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Modified Dai-Yuan iterative scheme for nonlinear systems and its application
1. | Department of Mathematical Sciences, Bayero University, Kano, Nigeria |
2. | Department of Mathematics, Sule Lamido University, Kafin Hausa, Nigeria |
3. | Department of Mathematics, Gombe state University, Gombe, Nigeria |
4. | Numerical Optimization Research Group, Bayero University, Kano, Nigeria |
By exploiting the idea employed in the spectral Dai-Yuan method by Xue et al. [IEICE Trans. Inf. Syst. 101 (12)2984-2990 (2018)] and the approach applied in the modified Hager-Zhang scheme for nonsmooth optimization [PLos ONE 11(10): e0164289 (2016)], we develop a Dai-Yuan type iterative scheme for convex constrained nonlinear monotone system. The scheme's algorithm is obtained by combining its search direction with the projection method [Kluwer Academic Publishers, pp. 355-369(1998)]. One of the new scheme's attribute is that it is derivative-free, which makes it ideal for solving non-smooth problems. Furthermore, we demonstrate the method's application in image de-blurring problems by comparing its performance with a recent effective method. By employing mild assumptions, global convergence of the scheme is determined and results of some numerical experiments show the method to be favorable compared to some recent iterative methods.
References:
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A. B. Abubakar, P. Kumam, H. Mohammad, A. M. Awwal and K. Sitthithakerngkiet,
A modified Fletcher-Reeves conjugate gradient method for monotone nonlinear equations with some applications, Mathematics, 7 (2019), 745.
doi: 10.3390/math7080745. |
[2] |
A. B. Abubakar, K. Muangchoo, A. H. Ibrahim, J. Abubakar and S. A. Rano,
FR-type algorithm for finding approximate solutions to nonlinear monotone operator equations, Arab. J. Math., 10 (2021), 261-270.
doi: 10.1007/s40065-021-00313-5. |
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S. Aji, P. Kumam, A. M. Awwal, M. M. Yahaya and K. Sitthithakerngkiet,
An efficient DY-type spectral conjugate gradient method for system nonlinear monotone equations with applications in signal recovery, AIMS Math., 6 (2021), 8078-8106.
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S. Babaie-Kafaki and R. Ghanbari,
A descent family of Dai-Liao conjugate gradient methods, Optim. Methods Softw., 29 (2013), 583-591.
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M. R. Banham and A. K. Katsaggelos,
Digital image restoration, IEEE Signal Process Mag., 14 (1997), 24-41.
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J. M. Barizilai and M. Borwein,
Two point step size gradient methods, IMA J. Numer. Anal., 8 (1988), 141-148.
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C. L. Chan, A. K. Katsaggelos and A. V. Sahakian,
Image sequence filtering in quantum-limited noise with applications to low-dose fluoroscopy, IEEE Trans. Med. Imaging, 12 (1993), 610-621.
|
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W. Cheng,
A two-term PRP-based descent method, Numer. Funct. Anal. Optim., 28 (2007), 1217-1230.
doi: 10.1080/01630560701749524. |
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W. Cheng,
A PRP type method for systems of monotone equations, Math. Comput. Modelling, 50 (2009), 15-20.
doi: 10.1016/j.mcm.2009.04.007. |
[10] |
W. La Cruz,
A spectral algorithm for large-scale systems of nonlinear monotone equations, Numer. Algor., 76 (2017), 1109-1130.
doi: 10.1007/s11075-017-0299-8. |
[11] |
W. La Cruz and M. Raydan,
Nonmonotone spectral methods for large-scale nonlinear systems, Optim. Methods Softw., 18 (2003), 583-599.
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Y. H. Dai and Y. Yuan,
A nonlinear conjugate gradient method with a strong global convergence property, SIAM J. Optim., 10 (1999), 177-182.
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A collection of nonlinear mixed complementarity problems, Optim. Methods Softw., 5 (1995), 319-345.
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Benchmarking optimization software with performance profiles, Math. Program., 91 (2002), 201-213.
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A. S. Halilu, A. Majumder, M. Y. Waziri and K. Ahmed,
Signal recovery with convex constrained nonlinear monotone equations through conjugate gradient hybrid approach, Math. Comput. Simulation, 187 (2021), 520-539.
doi: 10.1016/j.matcom.2021.03.020. |
[22] |
A. S. Halilu, A. Majumder, M. Y. Waziri, A. M. Awwal and K. Ahmed,
On solving double direction methods for convex constrained monotone nonlinear equations with image restoration, Comput. Appl. Math., 40 (2021), 239-265.
doi: 10.1007/s40314-021-01624-1. |
[23] |
B. S. He, H. Yang and S. L. Wang,
Alternationg direction method with self-adaptive penalty parameters for monotone variational inequalites, J. Optim. Theory Appl., 106 (2000), 337-356.
doi: 10.1023/A:1004603514434. |
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M. R. Hestenes and E. L. Stiefel,
Methods of conjugate gradients for solving linear systems, J. Research Nat. Bur. Standards, 49 (1952), 409-436.
|
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On a class of nonlinear integral equations arising in transport theory, SIAM J. Numer. Anal., 9 (1978), 787-792.
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D. H. Li and X. L. Wang,
A modified Fletcher-Reeves-type derivative-free method for symmetric nonlinear equations, Numer. Algebra, Control and Optimization, 1 (2011), 71-82.
doi: 10.3934/naco.2011.1.71. |
[27] |
Q. N. Li and D. H. Li,
A class of derivative-free methods for large-scale nonlinear monotone equations, IMA J. Numer. Anal., 31 (2011), 1625-1635.
doi: 10.1093/imanum/drq015. |
[28] |
J. Liu and Y. Feng,
A derivative-free iterative method for nonlinear monotone equations with convex constraints, Numer. Algor., 82 (2019), 245-262.
doi: 10.1007/s11075-018-0603-2. |
[29] |
J. K. Liu, J. L. Xu and L. Q. Zhang,
Partially symmetrical derivative-free Liu-Storey projection method for convex constrained equations, Inter. J. Comput. Math., 96 (2019), 1787-1798.
doi: 10.1080/00207160.2018.1533122. |
[30] |
J. K. Liu and S. J. Li,
A projection method for convex constrained monotone nonlinear equations with applications, Comput. Math. Appl., 70 (2015), 2442-2453.
doi: 10.1016/j.camwa.2015.09.014. |
[31] |
J. K. Liu and S. J. Li,
Spectral DY-type projection methods for nonlinear monotone system of equations, J. Comput. Math., 33 (2015), 341-355.
doi: 10.4208/jcm.1412-m4494. |
[32] |
J. K. Liu and S. J. Li,
Multivariate spectral projection method for convex constrained nonlinear monotone equations, Journal of Industrial and Management Optimization, 13 (2017), 283-297.
doi: 10.3934/jimo.2016017. |
[33] |
Y. Liu and C. Storey,
Efficient generalized conjugate gradient algorithms, Part 1: Theory, J. Optim. Theory Appl., 69 (1991), 129-137.
doi: 10.1007/BF00940464. |
[34] |
A. T. Mario, R. Figueiredo and D. Nowak,
An EM algorithm for wavelet-based image restoration, IEEE Transactions on Image Processing, 12 (2003), 906-916.
doi: 10.1109/TIP.2003.814255. |
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K. Meintjes and A. P. Morgan,
A methodology for solving chemical equilibrium systems, Appl. Math. Comput., 22 (1987), 333-361.
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J. S. Pang,
Inexact Newton methods for the nonlinear complementarity problem, Math. Program., 36 (1986), 54-71.
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G. Peiting and H. Chuanjiang, A derivative-free three-term projection algorithm involving spectral quotient for solving nonlinear monotone equations, Optimization, (2018) 1-18.
doi: 10.1080/02331934.2018.1482490. |
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E. Polak and G. Ribi$\acute{e}$re,
Note Sur la convergence de directions conjugèes, Rev. Francaise Informat. Recherche Operationelle, 3 (1969), 35-43.
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B. T. Polyak,
The conjugate gradient method in extreme problems, USSR Comp. Math. Math. Phys., 9 (1969), 94-112.
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J. Sabi'u, A. Shah and M. Y. Waziri,
Two optimal Hager-Zhang conjugate gradient methods for solving monotone nonlinear equations, Appl. Numer. Math., 153 (2020), 217-233.
doi: 10.1016/j.apnum.2020.02.017. |
[41] |
J. Sabi'u, A. Shah, M. Y. Waziri and K. Ahmed, Modified Hager-Zhang conjugate gradient methods via singular value analysis for solving monotone nonlinear equations with convex constraint, Int. J. Comput. Methods, 18 (2021), Paper No. 2050043, 33 pages.
doi: 10.1142/S0219876220500437. |
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C. H. Slump, Real-time image restoration in diagnostic X-ray imaging, the effects on quantum noise, in Proceedings 11th IAPR International Conference on Pattern Recognition, Vol.II. Conference B: Pattern Recognition Methodology and Systems, (1992), 693-696.
doi: 10.1109/ICPR.1992.201871. |
[43] |
V. M. Solodov and A. N. Iusem,
Newton-type methods with generalized distances for constrained optimization, Optimization, 41 (1997), 257-277.
doi: 10.1080/02331939708844339. |
[44] |
M. V. Solodov and B. F. Svaiter, A globally convergent inexact Newton method for systems of monotone equations, in Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods (eds. M. Fukushima, L. Qi), Kluwer Academic Publishers, (1998), 355-369.
doi: 10.1007/978-1-4757-6388-1_18. |
[45] |
C. W. Wang, Y. J. Wang and C. L. Xu,
A projection method for a system of nonlinear monotone equations with convex constraints, Math. Meth. Oper. Res., 66 (2007), 33-46.
doi: 10.1007/s00186-006-0140-y. |
[46] |
X. Y. Wang, X. J. Li and X. P. Kou,
A self-adaptive three-term conjugate gradient method for monotone nonlinear equations with convex constraints, Calcolo, 53 (2016), 133-145.
doi: 10.1007/s10092-015-0140-5. |
[47] |
M. Y. Waziri, K. Ahmed and J. Sabi'u,
A family of Hager-Zhang conjugate gradient methods for system of monotone nonlinear equations, Appl. Math. Comput., 361 (2019), 645-660.
doi: 10.1016/j.amc.2019.06.012. |
[48] |
M. Y. Waziri, K. Ahmed and J. Sabi'u,
A Dai-Liao conjugate gradient method via modified secant equation for system of nonlinear equations, Arab. J. Math., 9 (2020), 443-457.
doi: 10.1007/s40065-019-0264-6. |
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M. Y. Waziri, K. Ahmed and J. Sabi'u,
Descent Perry conjugate gradient methods for systems of monotone nonlinear equations, Numer. Algor., 85 (2020), 763-785.
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Y. Xiao, Q. Wang and Q. Hu,
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W. Xue, J. Ren, X. Zheng, Z. Liu and Y. Liang,
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show all references
References:
[1] |
A. B. Abubakar, P. Kumam, H. Mohammad, A. M. Awwal and K. Sitthithakerngkiet,
A modified Fletcher-Reeves conjugate gradient method for monotone nonlinear equations with some applications, Mathematics, 7 (2019), 745.
doi: 10.3390/math7080745. |
[2] |
A. B. Abubakar, K. Muangchoo, A. H. Ibrahim, J. Abubakar and S. A. Rano,
FR-type algorithm for finding approximate solutions to nonlinear monotone operator equations, Arab. J. Math., 10 (2021), 261-270.
doi: 10.1007/s40065-021-00313-5. |
[3] |
S. Aji, P. Kumam, A. M. Awwal, M. M. Yahaya and K. Sitthithakerngkiet,
An efficient DY-type spectral conjugate gradient method for system nonlinear monotone equations with applications in signal recovery, AIMS Math., 6 (2021), 8078-8106.
doi: 10.3934/math.2021469. |
[4] |
S. Babaie-Kafaki and R. Ghanbari,
A descent family of Dai-Liao conjugate gradient methods, Optim. Methods Softw., 29 (2013), 583-591.
doi: 10.1080/10556788.2013.833199. |
[5] |
M. R. Banham and A. K. Katsaggelos,
Digital image restoration, IEEE Signal Process Mag., 14 (1997), 24-41.
doi: 10.1109/79.581363. |
[6] |
J. M. Barizilai and M. Borwein,
Two point step size gradient methods, IMA J. Numer. Anal., 8 (1988), 141-148.
doi: 10.1093/imanum/8.1.141. |
[7] |
C. L. Chan, A. K. Katsaggelos and A. V. Sahakian,
Image sequence filtering in quantum-limited noise with applications to low-dose fluoroscopy, IEEE Trans. Med. Imaging, 12 (1993), 610-621.
|
[8] |
W. Cheng,
A two-term PRP-based descent method, Numer. Funct. Anal. Optim., 28 (2007), 1217-1230.
doi: 10.1080/01630560701749524. |
[9] |
W. Cheng,
A PRP type method for systems of monotone equations, Math. Comput. Modelling, 50 (2009), 15-20.
doi: 10.1016/j.mcm.2009.04.007. |
[10] |
W. La Cruz,
A spectral algorithm for large-scale systems of nonlinear monotone equations, Numer. Algor., 76 (2017), 1109-1130.
doi: 10.1007/s11075-017-0299-8. |
[11] |
W. La Cruz and M. Raydan,
Nonmonotone spectral methods for large-scale nonlinear systems, Optim. Methods Softw., 18 (2003), 583-599.
doi: 10.1080/10556780310001610493. |
[12] |
Y. H. Dai and Y. Yuan,
A nonlinear conjugate gradient method with a strong global convergence property, SIAM J. Optim., 10 (1999), 177-182.
doi: 10.1137/S1052623497318992. |
[13] |
S. P. Dirkse and M. C. Ferris,
A collection of nonlinear mixed complementarity problems, Optim. Methods Softw., 5 (1995), 319-345.
|
[14] |
E. D. Dolan and J. J. Moré,
Benchmarking optimization software with performance profiles, Math. Program., 91 (2002), 201-213.
doi: 10.1007/s101070100263. |
[15] |
T. Elaine, Y. Wotao and Z. Yin, A fixed-point continuation method for $\ell_1-$regularized minimization with applications to compressed sensing, CAAM TR07-07, Rice University, (2007), 43-44. |
[16] |
M. Figueiredo, R. Nowak and S. J. Wright, Gradient projection for sparse reconstruction, application to compressed sensing and other inverse problems, IEEE J-STSP, IEEE Press, Piscataway, NJ. (2007), 586-597. |
[17] |
R. Fletcher and C. Reeves,
Function minimization by conjugate gradients, The Computer Journal, 7 (1964), 149-154.
doi: 10.1093/comjnl/7.2.149. |
[18] |
R. Fletcher, Practical Method of Optimization, Volume 1: Unconstrained Optimization, 2nd edition, Wiley, New York, 1997. |
[19] |
W. W. Hager and H. Zhang,
A new conjugate gradient method with guaranteed descent and an efficient line search, SIAM J. Optim., 16 (2005), 170-192.
doi: 10.1137/030601880. |
[20] |
A. S. Halilu and M. Y. Waziri,
An improved derivative-free method via double direction approach for solving systems of nonlinear equations, J. Ramanujan Math. Soc., 33 (2018), 75-89.
doi: 10.1007/s00180-017-0741-3. |
[21] |
A. S. Halilu, A. Majumder, M. Y. Waziri and K. Ahmed,
Signal recovery with convex constrained nonlinear monotone equations through conjugate gradient hybrid approach, Math. Comput. Simulation, 187 (2021), 520-539.
doi: 10.1016/j.matcom.2021.03.020. |
[22] |
A. S. Halilu, A. Majumder, M. Y. Waziri, A. M. Awwal and K. Ahmed,
On solving double direction methods for convex constrained monotone nonlinear equations with image restoration, Comput. Appl. Math., 40 (2021), 239-265.
doi: 10.1007/s40314-021-01624-1. |
[23] |
B. S. He, H. Yang and S. L. Wang,
Alternationg direction method with self-adaptive penalty parameters for monotone variational inequalites, J. Optim. Theory Appl., 106 (2000), 337-356.
doi: 10.1023/A:1004603514434. |
[24] |
M. R. Hestenes and E. L. Stiefel,
Methods of conjugate gradients for solving linear systems, J. Research Nat. Bur. Standards, 49 (1952), 409-436.
|
[25] |
G. A. Hively,
On a class of nonlinear integral equations arising in transport theory, SIAM J. Numer. Anal., 9 (1978), 787-792.
doi: 10.1137/0509060. |
[26] |
D. H. Li and X. L. Wang,
A modified Fletcher-Reeves-type derivative-free method for symmetric nonlinear equations, Numer. Algebra, Control and Optimization, 1 (2011), 71-82.
doi: 10.3934/naco.2011.1.71. |
[27] |
Q. N. Li and D. H. Li,
A class of derivative-free methods for large-scale nonlinear monotone equations, IMA J. Numer. Anal., 31 (2011), 1625-1635.
doi: 10.1093/imanum/drq015. |
[28] |
J. Liu and Y. Feng,
A derivative-free iterative method for nonlinear monotone equations with convex constraints, Numer. Algor., 82 (2019), 245-262.
doi: 10.1007/s11075-018-0603-2. |
[29] |
J. K. Liu, J. L. Xu and L. Q. Zhang,
Partially symmetrical derivative-free Liu-Storey projection method for convex constrained equations, Inter. J. Comput. Math., 96 (2019), 1787-1798.
doi: 10.1080/00207160.2018.1533122. |
[30] |
J. K. Liu and S. J. Li,
A projection method for convex constrained monotone nonlinear equations with applications, Comput. Math. Appl., 70 (2015), 2442-2453.
doi: 10.1016/j.camwa.2015.09.014. |
[31] |
J. K. Liu and S. J. Li,
Spectral DY-type projection methods for nonlinear monotone system of equations, J. Comput. Math., 33 (2015), 341-355.
doi: 10.4208/jcm.1412-m4494. |
[32] |
J. K. Liu and S. J. Li,
Multivariate spectral projection method for convex constrained nonlinear monotone equations, Journal of Industrial and Management Optimization, 13 (2017), 283-297.
doi: 10.3934/jimo.2016017. |
[33] |
Y. Liu and C. Storey,
Efficient generalized conjugate gradient algorithms, Part 1: Theory, J. Optim. Theory Appl., 69 (1991), 129-137.
doi: 10.1007/BF00940464. |
[34] |
A. T. Mario, R. Figueiredo and D. Nowak,
An EM algorithm for wavelet-based image restoration, IEEE Transactions on Image Processing, 12 (2003), 906-916.
doi: 10.1109/TIP.2003.814255. |
[35] |
K. Meintjes and A. P. Morgan,
A methodology for solving chemical equilibrium systems, Appl. Math. Comput., 22 (1987), 333-361.
doi: 10.1016/0096-3003(87)90076-2. |
[36] |
J. S. Pang,
Inexact Newton methods for the nonlinear complementarity problem, Math. Program., 36 (1986), 54-71.
doi: 10.1007/BF02591989. |
[37] |
G. Peiting and H. Chuanjiang, A derivative-free three-term projection algorithm involving spectral quotient for solving nonlinear monotone equations, Optimization, (2018) 1-18.
doi: 10.1080/02331934.2018.1482490. |
[38] |
E. Polak and G. Ribi$\acute{e}$re,
Note Sur la convergence de directions conjugèes, Rev. Francaise Informat. Recherche Operationelle, 3 (1969), 35-43.
|
[39] |
B. T. Polyak,
The conjugate gradient method in extreme problems, USSR Comp. Math. Math. Phys., 9 (1969), 94-112.
|
[40] |
J. Sabi'u, A. Shah and M. Y. Waziri,
Two optimal Hager-Zhang conjugate gradient methods for solving monotone nonlinear equations, Appl. Numer. Math., 153 (2020), 217-233.
doi: 10.1016/j.apnum.2020.02.017. |
[41] |
J. Sabi'u, A. Shah, M. Y. Waziri and K. Ahmed, Modified Hager-Zhang conjugate gradient methods via singular value analysis for solving monotone nonlinear equations with convex constraint, Int. J. Comput. Methods, 18 (2021), Paper No. 2050043, 33 pages.
doi: 10.1142/S0219876220500437. |
[42] |
C. H. Slump, Real-time image restoration in diagnostic X-ray imaging, the effects on quantum noise, in Proceedings 11th IAPR International Conference on Pattern Recognition, Vol.II. Conference B: Pattern Recognition Methodology and Systems, (1992), 693-696.
doi: 10.1109/ICPR.1992.201871. |
[43] |
V. M. Solodov and A. N. Iusem,
Newton-type methods with generalized distances for constrained optimization, Optimization, 41 (1997), 257-277.
doi: 10.1080/02331939708844339. |
[44] |
M. V. Solodov and B. F. Svaiter, A globally convergent inexact Newton method for systems of monotone equations, in Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods (eds. M. Fukushima, L. Qi), Kluwer Academic Publishers, (1998), 355-369.
doi: 10.1007/978-1-4757-6388-1_18. |
[45] |
C. W. Wang, Y. J. Wang and C. L. Xu,
A projection method for a system of nonlinear monotone equations with convex constraints, Math. Meth. Oper. Res., 66 (2007), 33-46.
doi: 10.1007/s00186-006-0140-y. |
[46] |
X. Y. Wang, X. J. Li and X. P. Kou,
A self-adaptive three-term conjugate gradient method for monotone nonlinear equations with convex constraints, Calcolo, 53 (2016), 133-145.
doi: 10.1007/s10092-015-0140-5. |
[47] |
M. Y. Waziri, K. Ahmed and J. Sabi'u,
A family of Hager-Zhang conjugate gradient methods for system of monotone nonlinear equations, Appl. Math. Comput., 361 (2019), 645-660.
doi: 10.1016/j.amc.2019.06.012. |
[48] |
M. Y. Waziri, K. Ahmed and J. Sabi'u,
A Dai-Liao conjugate gradient method via modified secant equation for system of nonlinear equations, Arab. J. Math., 9 (2020), 443-457.
doi: 10.1007/s40065-019-0264-6. |
[49] |
M. Y. Waziri, K. Ahmed and J. Sabi'u,
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Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 6 | 12 | 0.27234 | 2.0475E-09 | 16 | 35 | 0.30469 | 4.1222E-09 | 11 | 25 | 0.13273 | 2.4989E-09 | 26 | 106 | 0.36405 | 0.0000E+00 | |||
5000 | x2 | 6 | 12 | 0.07889 | 4.0428E-09 | 16 | 35 | 0.05510 | 8.2456E-09 | 12 | 28 | 0.05936 | 2.2971E-09 | 26 | 106 | 0.12459 | 0.0000E+00 | |||
5000 | x3 | 3 | 5 | 0.01436 | 8.4985E-09 | 18 | 39 | 0.06173 | 4.5974E-09 | 12 | 28 | 0.07119 | 5.7248E-09 | 30 | 122 | 0.17739 | 0.0000E+00 | |||
5000 | x4 | 5 | 9 | 0.02079 | 1.8997E-09 | 20 | 43 | 0.06536 | 4.6462E-09 | 14 | 34 | 0.05971 | 2.5758E-09 | 34 | 138 | 0.16181 | 0.0000E+00 | |||
5000 | x5 | 11 | 23 | 0.03935 | 3.9754E-10 | 20 | 43 | 0.07339 | 8.5913E-09 | 15 | 37 | 0.05510 | 2.6441E-09 | 36 | 146 | 0.18173 | 0.0000E+00 | |||
5000 | x6 | 20 | 45 | 0.08341 | 8.4879E-09 | 21 | 45 | 0.07166 | 3.4438E-09 | 15 | 36 | 0.06630 | 5.1003E-09 | 35 | 141 | 0.17659 | 0.0000E+00 | |||
5000 | x7 | 12 | 25 | 0.05233 | 5.4026E-10 | 21 | 46 | 0.08474 | 4.3326E-09 | 15 | 39 | 0.09094 | 5.0139E-09 | 35 | 142 | 0.16383 | 0.0000E+00 | |||
5000 | x8 | 10 | 21 | 0.04351 | 9.5806E-09 | 21 | 46 | 0.07816 | 5.2005E-09 | 15 | 41 | 0.07043 | 4.5835E-09 | 35 | 142 | 0.18567 | 0.0000E+00 | |||
10000 | x1 | 6 | 12 | 0.04366 | 2.8956E-09 | 16 | 35 | 0.11302 | 5.8297E-09 | 10 | 23 | 0.05868 | 8.5342E-09 | 26 | 106 | 0.22574 | 0.0000E+00 | |||
10000 | x2 | 6 | 12 | 0.04652 | 5.7173E-09 | 17 | 37 | 0.10115 | 3.8700E-09 | 12 | 28 | 0.13233 | 3.1978E-09 | 26 | 106 | 0.25446 | 0.0000E+00 | |||
10000 | x3 | 4 | 6 | 0.02748 | 5.9571E-10 | 18 | 39 | 0.10617 | 6.5017E-09 | 12 | 28 | 0.08322 | 3.7136E-09 | 30 | 122 | 0.25620 | 0.0000E+00 | |||
10000 | x4 | 5 | 9 | 0.03605 | 2.6866E-09 | 20 | 43 | 0.12137 | 6.5707E-09 | 14 | 33 | 0.10267 | 4.4531E-09 | 34 | 138 | 0.26421 | 0.0000E+00 | |||
10000 | x5 | 11 | 23 | 0.09120 | 5.6221E-10 | 21 | 45 | 0.12382 | 4.0482E-09 | 15 | 37 | 0.11103 | 5.1673E-09 | 36 | 146 | 0.31887 | 0.0000E+00 | |||
10000 | x6 | 21 | 48 | 0.14197 | 6.1811E-09 | 20 | 44 | 0.15292 | 5.5936E-09 | 16 | 39 | 0.12905 | 3.0303E-09 | 35 | 141 | 0.31019 | 0.0000E+00 | |||
10000 | x7 | 12 | 25 | 0.08928 | 7.6404E-10 | 21 | 46 | 0.13180 | 6.1272E-09 | 16 | 43 | 0.12267 | 3.0885E-09 | 35 | 142 | 0.29184 | 0.0000E+00 | |||
10000 | x8 | 11 | 22 | 0.07167 | 3.5449E-10 | 21 | 47 | 0.12698 | 7.3547E-09 | 15 | 41 | 0.14901 | 2.9293E-09 | 35 | 142 | 0.29874 | 0.0000E+00 | |||
50000 | x1 | 6 | 12 | 0.18477 | 6.4748E-09 | 17 | 37 | 0.43468 | 4.3261E-09 | 12 | 28 | 0.31329 | 3.4966E-09 | 26 | 106 | 1.02635 | 0.0000E+00 | |||
50000 | x2 | 7 | 13 | 0.18950 | 4.9344E-10 | 17 | 37 | 0.39080 | 8.6535E-09 | 12 | 28 | 0.32265 | 5.2020E-09 | 26 | 106 | 0.99223 | 0.0000E+00 | |||
50000 | x3 | 4 | 6 | 0.09771 | 1.3320E-09 | 19 | 41 | 0.47699 | 4.8342E-09 | 13 | 31 | 0.37285 | 4.4055E-09 | 30 | 122 | 1.16776 | 0.0000E+00 | |||
50000 | x4 | 5 | 9 | 0.13988 | 6.0075E-09 | 21 | 45 | 0.48957 | 4.8925E-09 | 16 | 42 | 0.43939 | 2.3366E-09 | 34 | 138 | 1.26896 | 0.0000E+00 | |||
50000 | x5 | 11 | 23 | 0.29815 | 1.2571E-09 | 23 | 53 | 0.54401 | 5.3731E-09 | 18 | 52 | 0.53469 | 2.9724E-09 | 36 | 146 | 1.33839 | 0.0000E+00 | |||
50000 | x6 | 22 | 51 | 0.55331 | 7.5655E-09 | 23 | 54 | 0.54909 | 7.2056E-09 | 19 | 55 | 0.59269 | 3.2582E-09 | 35 | 141 | 1.28348 | 0.0000E+00 | |||
50000 | x7 | 12 | 25 | 0.32319 | 1.7085E-09 | 23 | 54 | 0.58040 | 4.9765E-09 | 19 | 61 | 0.60155 | 3.3731E-09 | 35 | 142 | 1.33907 | 0.0000E+00 | |||
50000 | x8 | 11 | 22 | 0.26948 | 7.9265E-10 | 23 | 54 | 0.56286 | 5.4177E-09 | 18 | 56 | 0.56586 | 2.7351E-09 | 35 | 142 | 1.31569 | 0.0000E+00 |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 6 | 12 | 0.27234 | 2.0475E-09 | 16 | 35 | 0.30469 | 4.1222E-09 | 11 | 25 | 0.13273 | 2.4989E-09 | 26 | 106 | 0.36405 | 0.0000E+00 | |||
5000 | x2 | 6 | 12 | 0.07889 | 4.0428E-09 | 16 | 35 | 0.05510 | 8.2456E-09 | 12 | 28 | 0.05936 | 2.2971E-09 | 26 | 106 | 0.12459 | 0.0000E+00 | |||
5000 | x3 | 3 | 5 | 0.01436 | 8.4985E-09 | 18 | 39 | 0.06173 | 4.5974E-09 | 12 | 28 | 0.07119 | 5.7248E-09 | 30 | 122 | 0.17739 | 0.0000E+00 | |||
5000 | x4 | 5 | 9 | 0.02079 | 1.8997E-09 | 20 | 43 | 0.06536 | 4.6462E-09 | 14 | 34 | 0.05971 | 2.5758E-09 | 34 | 138 | 0.16181 | 0.0000E+00 | |||
5000 | x5 | 11 | 23 | 0.03935 | 3.9754E-10 | 20 | 43 | 0.07339 | 8.5913E-09 | 15 | 37 | 0.05510 | 2.6441E-09 | 36 | 146 | 0.18173 | 0.0000E+00 | |||
5000 | x6 | 20 | 45 | 0.08341 | 8.4879E-09 | 21 | 45 | 0.07166 | 3.4438E-09 | 15 | 36 | 0.06630 | 5.1003E-09 | 35 | 141 | 0.17659 | 0.0000E+00 | |||
5000 | x7 | 12 | 25 | 0.05233 | 5.4026E-10 | 21 | 46 | 0.08474 | 4.3326E-09 | 15 | 39 | 0.09094 | 5.0139E-09 | 35 | 142 | 0.16383 | 0.0000E+00 | |||
5000 | x8 | 10 | 21 | 0.04351 | 9.5806E-09 | 21 | 46 | 0.07816 | 5.2005E-09 | 15 | 41 | 0.07043 | 4.5835E-09 | 35 | 142 | 0.18567 | 0.0000E+00 | |||
10000 | x1 | 6 | 12 | 0.04366 | 2.8956E-09 | 16 | 35 | 0.11302 | 5.8297E-09 | 10 | 23 | 0.05868 | 8.5342E-09 | 26 | 106 | 0.22574 | 0.0000E+00 | |||
10000 | x2 | 6 | 12 | 0.04652 | 5.7173E-09 | 17 | 37 | 0.10115 | 3.8700E-09 | 12 | 28 | 0.13233 | 3.1978E-09 | 26 | 106 | 0.25446 | 0.0000E+00 | |||
10000 | x3 | 4 | 6 | 0.02748 | 5.9571E-10 | 18 | 39 | 0.10617 | 6.5017E-09 | 12 | 28 | 0.08322 | 3.7136E-09 | 30 | 122 | 0.25620 | 0.0000E+00 | |||
10000 | x4 | 5 | 9 | 0.03605 | 2.6866E-09 | 20 | 43 | 0.12137 | 6.5707E-09 | 14 | 33 | 0.10267 | 4.4531E-09 | 34 | 138 | 0.26421 | 0.0000E+00 | |||
10000 | x5 | 11 | 23 | 0.09120 | 5.6221E-10 | 21 | 45 | 0.12382 | 4.0482E-09 | 15 | 37 | 0.11103 | 5.1673E-09 | 36 | 146 | 0.31887 | 0.0000E+00 | |||
10000 | x6 | 21 | 48 | 0.14197 | 6.1811E-09 | 20 | 44 | 0.15292 | 5.5936E-09 | 16 | 39 | 0.12905 | 3.0303E-09 | 35 | 141 | 0.31019 | 0.0000E+00 | |||
10000 | x7 | 12 | 25 | 0.08928 | 7.6404E-10 | 21 | 46 | 0.13180 | 6.1272E-09 | 16 | 43 | 0.12267 | 3.0885E-09 | 35 | 142 | 0.29184 | 0.0000E+00 | |||
10000 | x8 | 11 | 22 | 0.07167 | 3.5449E-10 | 21 | 47 | 0.12698 | 7.3547E-09 | 15 | 41 | 0.14901 | 2.9293E-09 | 35 | 142 | 0.29874 | 0.0000E+00 | |||
50000 | x1 | 6 | 12 | 0.18477 | 6.4748E-09 | 17 | 37 | 0.43468 | 4.3261E-09 | 12 | 28 | 0.31329 | 3.4966E-09 | 26 | 106 | 1.02635 | 0.0000E+00 | |||
50000 | x2 | 7 | 13 | 0.18950 | 4.9344E-10 | 17 | 37 | 0.39080 | 8.6535E-09 | 12 | 28 | 0.32265 | 5.2020E-09 | 26 | 106 | 0.99223 | 0.0000E+00 | |||
50000 | x3 | 4 | 6 | 0.09771 | 1.3320E-09 | 19 | 41 | 0.47699 | 4.8342E-09 | 13 | 31 | 0.37285 | 4.4055E-09 | 30 | 122 | 1.16776 | 0.0000E+00 | |||
50000 | x4 | 5 | 9 | 0.13988 | 6.0075E-09 | 21 | 45 | 0.48957 | 4.8925E-09 | 16 | 42 | 0.43939 | 2.3366E-09 | 34 | 138 | 1.26896 | 0.0000E+00 | |||
50000 | x5 | 11 | 23 | 0.29815 | 1.2571E-09 | 23 | 53 | 0.54401 | 5.3731E-09 | 18 | 52 | 0.53469 | 2.9724E-09 | 36 | 146 | 1.33839 | 0.0000E+00 | |||
50000 | x6 | 22 | 51 | 0.55331 | 7.5655E-09 | 23 | 54 | 0.54909 | 7.2056E-09 | 19 | 55 | 0.59269 | 3.2582E-09 | 35 | 141 | 1.28348 | 0.0000E+00 | |||
50000 | x7 | 12 | 25 | 0.32319 | 1.7085E-09 | 23 | 54 | 0.58040 | 4.9765E-09 | 19 | 61 | 0.60155 | 3.3731E-09 | 35 | 142 | 1.33907 | 0.0000E+00 | |||
50000 | x8 | 11 | 22 | 0.26948 | 7.9265E-10 | 23 | 54 | 0.56286 | 5.4177E-09 | 18 | 56 | 0.56586 | 2.7351E-09 | 35 | 142 | 1.31569 | 0.0000E+00 |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 1 | 2 | 0.01078 | 0.0000E+00 | 1 | 2 | 0.01097 | 0.0000E+00 | 1 | 2 | 0.01014 | 0.0000E+00 | 1 | 2 | 0.01003 | 0.0000E+00 | |||
5000 | x2 | 1 | 2 | 0.02040 | 0.0000E+00 | 1 | 2 | 0.00944 | 0.0000E+00 | 1 | 2 | 0.01005 | 0.0000E+00 | 1 | 2 | 0.02019 | 0.0000E+00 | |||
5000 | x3 | 1 | 2 | 0.01013 | 0.0000E+00 | 1 | 2 | 0.00965 | 0.0000E+00 | 1 | 2 | 0.00947 | 0.0000E+00 | 1 | 2 | 0.01038 | 0.0000E+00 | |||
5000 | x4 | 1 | 2 | 0.00951 | 0.0000E+00 | 1 | 2 | 0.00966 | 0.0000E+00 | 1 | 2 | 0.00928 | 0.0000E+00 | ** | ** | ** | ** | |||
5000 | x5 | 1 | 2 | 0.01045 | 0.0000E+00 | 1 | 2 | 0.00748 | 0.0000E+00 | 1 | 2 | 0.00649 | 0.0000E+00 | 1 | 2 | 0.00520 | 0.0000E+00 | |||
5000 | x6 | 1 | 2 | 0.00940 | 0.0000E+00 | 1 | 2 | 0.00732 | 0.0000E+00 | 1 | 2 | 0.00662 | 0.0000E+00 | 1 | 2 | 0.00842 | 0.0000E+00 | |||
5000 | x7 | 1 | 2 | 0.00979 | 0.0000E+00 | 1 | 2 | 0.00660 | 0.0000E+00 | 1 | 2 | 0.00667 | 0.0000E+00 | 1 | 2 | 0.00757 | 0.0000E+00 | |||
5000 | x8 | 1 | 2 | 0.01111 | 0.0000E+00 | 1 | 2 | 0.00795 | 0.0000E+00 | 1 | 2 | 0.00687 | 0.0000E+00 | 1 | 2 | 0.00779 | 0.0000E+00 | |||
10000 | x1 | 1 | 2 | 0.01478 | 0.0000E+00 | 1 | 2 | 0.01622 | 0.0000E+00 | 1 | 2 | 0.01650 | 0.0000E+00 | 1 | 2 | 0.01449 | 0.0000E+00 | |||
10000 | x2 | 1 | 2 | 0.01571 | 0.0000E+00 | 1 | 2 | 0.01633 | 0.0000E+00 | 1 | 2 | 0.01488 | 0.0000E+00 | 1 | 2 | 0.01594 | 0.0000E+00 | |||
10000 | x3 | 1 | 2 | 0.01490 | 0.0000E+00 | 1 | 2 | 0.02384 | 0.0000E+00 | 1 | 2 | 0.03357 | 0.0000E+00 | 1 | 2 | 0.01579 | 0.0000E+00 | |||
10000 | x4 | 1 | 2 | 0.01739 | 0.0000E+00 | 1 | 2 | 0.01549 | 0.0000E+00 | 1 | 3 | 0.02037 | 0.0000E+00 | ** | ** | ** | ** | |||
10000 | x5 | 1 | 2 | 0.01636 | 0.0000E+00 | 1 | 2 | 0.01000 | 0.0000E+00 | 1 | 2 | 0.01013 | 0.0000E+00 | 1 | 2 | 0.00759 | 0.0000E+00 | |||
10000 | x6 | 1 | 2 | 0.01637 | 0.0000E+00 | 1 | 2 | 0.00939 | 0.0000E+00 | 1 | 2 | 0.01043 | 0.0000E+00 | 1 | 2 | 0.01118 | 0.0000E+00 | |||
10000 | x7 | 1 | 2 | 0.01602 | 0.0000E+00 | 1 | 2 | 0.00893 | 0.0000E+00 | 1 | 2 | 0.00994 | 0.0000E+00 | 1 | 2 | 0.01012 | 0.0000E+00 | |||
10000 | x8 | 1 | 2 | 0.01539 | 0.0000E+00 | 1 | 2 | 0.01026 | 0.0000E+00 | 1 | 2 | 0.01045 | 0.0000E+00 | 1 | 2 | 0.01100 | 0.0000E+00 | |||
50000 | x1 | 1 | 2 | 0.05796 | 0.0000E+00 | 1 | 2 | 0.06032 | 0.0000E+00 | 1 | 2 | 0.06280 | 0.0000E+00 | 1 | 2 | 0.05899 | 0.0000E+00 | |||
50000 | x2 | 1 | 2 | 0.06203 | 0.0000E+00 | 1 | 2 | 0.05772 | 0.0000E+00 | 1 | 2 | 0.06076 | 0.0000E+00 | 1 | 2 | 0.05922 | 0.0000E+00 | |||
50000 | x3 | 1 | 2 | 0.05224 | 0.0000E+00 | 1 | 2 | 0.05857 | 0.0000E+00 | 1 | 2 | 0.06821 | 0.0000E+00 | 1 | 2 | 0.06629 | 0.0000E+00 | |||
50000 | x4 | 1 | 2 | 0.06079 | 0.0000E+00 | 1 | 3 | 0.07697 | 0.0000E+00 | 1 | 5 | 0.11996 | 0.0000E+00 | ** | ** | ** | ** | |||
50000 | x5 | 1 | 2 | 0.06053 | 0.0000E+00 | 1 | 2 | 0.03772 | 0.0000E+00 | 1 | 2 | 0.03890 | 0.0000E+00 | 1 | 2 | 0.03026 | 0.0000E+00 | |||
50000 | x6 | 1 | 2 | 0.05694 | 0.0000E+00 | 1 | 2 | 0.03597 | 0.0000E+00 | 1 | 2 | 0.03897 | 0.0000E+00 | 1 | 2 | 0.03691 | 0.0000E+00 | |||
50000 | x7 | 1 | 2 | 0.06281 | 0.0000E+00 | 1 | 2 | 0.03922 | 0.0000E+00 | 1 | 2 | 0.03959 | 0.0000E+00 | 1 | 2 | 0.03842 | 0.0000E+00 | |||
50000 | x8 | 1 | 2 | 0.05664 | 0.0000E+00 | 1 | 2 | 0.03785 | 0.0000E+00 | 1 | 2 | 0.03866 | 0.0000E+00 | 1 | 2 | 0.04029 | 0.0000E+00 |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 1 | 2 | 0.01078 | 0.0000E+00 | 1 | 2 | 0.01097 | 0.0000E+00 | 1 | 2 | 0.01014 | 0.0000E+00 | 1 | 2 | 0.01003 | 0.0000E+00 | |||
5000 | x2 | 1 | 2 | 0.02040 | 0.0000E+00 | 1 | 2 | 0.00944 | 0.0000E+00 | 1 | 2 | 0.01005 | 0.0000E+00 | 1 | 2 | 0.02019 | 0.0000E+00 | |||
5000 | x3 | 1 | 2 | 0.01013 | 0.0000E+00 | 1 | 2 | 0.00965 | 0.0000E+00 | 1 | 2 | 0.00947 | 0.0000E+00 | 1 | 2 | 0.01038 | 0.0000E+00 | |||
5000 | x4 | 1 | 2 | 0.00951 | 0.0000E+00 | 1 | 2 | 0.00966 | 0.0000E+00 | 1 | 2 | 0.00928 | 0.0000E+00 | ** | ** | ** | ** | |||
5000 | x5 | 1 | 2 | 0.01045 | 0.0000E+00 | 1 | 2 | 0.00748 | 0.0000E+00 | 1 | 2 | 0.00649 | 0.0000E+00 | 1 | 2 | 0.00520 | 0.0000E+00 | |||
5000 | x6 | 1 | 2 | 0.00940 | 0.0000E+00 | 1 | 2 | 0.00732 | 0.0000E+00 | 1 | 2 | 0.00662 | 0.0000E+00 | 1 | 2 | 0.00842 | 0.0000E+00 | |||
5000 | x7 | 1 | 2 | 0.00979 | 0.0000E+00 | 1 | 2 | 0.00660 | 0.0000E+00 | 1 | 2 | 0.00667 | 0.0000E+00 | 1 | 2 | 0.00757 | 0.0000E+00 | |||
5000 | x8 | 1 | 2 | 0.01111 | 0.0000E+00 | 1 | 2 | 0.00795 | 0.0000E+00 | 1 | 2 | 0.00687 | 0.0000E+00 | 1 | 2 | 0.00779 | 0.0000E+00 | |||
10000 | x1 | 1 | 2 | 0.01478 | 0.0000E+00 | 1 | 2 | 0.01622 | 0.0000E+00 | 1 | 2 | 0.01650 | 0.0000E+00 | 1 | 2 | 0.01449 | 0.0000E+00 | |||
10000 | x2 | 1 | 2 | 0.01571 | 0.0000E+00 | 1 | 2 | 0.01633 | 0.0000E+00 | 1 | 2 | 0.01488 | 0.0000E+00 | 1 | 2 | 0.01594 | 0.0000E+00 | |||
10000 | x3 | 1 | 2 | 0.01490 | 0.0000E+00 | 1 | 2 | 0.02384 | 0.0000E+00 | 1 | 2 | 0.03357 | 0.0000E+00 | 1 | 2 | 0.01579 | 0.0000E+00 | |||
10000 | x4 | 1 | 2 | 0.01739 | 0.0000E+00 | 1 | 2 | 0.01549 | 0.0000E+00 | 1 | 3 | 0.02037 | 0.0000E+00 | ** | ** | ** | ** | |||
10000 | x5 | 1 | 2 | 0.01636 | 0.0000E+00 | 1 | 2 | 0.01000 | 0.0000E+00 | 1 | 2 | 0.01013 | 0.0000E+00 | 1 | 2 | 0.00759 | 0.0000E+00 | |||
10000 | x6 | 1 | 2 | 0.01637 | 0.0000E+00 | 1 | 2 | 0.00939 | 0.0000E+00 | 1 | 2 | 0.01043 | 0.0000E+00 | 1 | 2 | 0.01118 | 0.0000E+00 | |||
10000 | x7 | 1 | 2 | 0.01602 | 0.0000E+00 | 1 | 2 | 0.00893 | 0.0000E+00 | 1 | 2 | 0.00994 | 0.0000E+00 | 1 | 2 | 0.01012 | 0.0000E+00 | |||
10000 | x8 | 1 | 2 | 0.01539 | 0.0000E+00 | 1 | 2 | 0.01026 | 0.0000E+00 | 1 | 2 | 0.01045 | 0.0000E+00 | 1 | 2 | 0.01100 | 0.0000E+00 | |||
50000 | x1 | 1 | 2 | 0.05796 | 0.0000E+00 | 1 | 2 | 0.06032 | 0.0000E+00 | 1 | 2 | 0.06280 | 0.0000E+00 | 1 | 2 | 0.05899 | 0.0000E+00 | |||
50000 | x2 | 1 | 2 | 0.06203 | 0.0000E+00 | 1 | 2 | 0.05772 | 0.0000E+00 | 1 | 2 | 0.06076 | 0.0000E+00 | 1 | 2 | 0.05922 | 0.0000E+00 | |||
50000 | x3 | 1 | 2 | 0.05224 | 0.0000E+00 | 1 | 2 | 0.05857 | 0.0000E+00 | 1 | 2 | 0.06821 | 0.0000E+00 | 1 | 2 | 0.06629 | 0.0000E+00 | |||
50000 | x4 | 1 | 2 | 0.06079 | 0.0000E+00 | 1 | 3 | 0.07697 | 0.0000E+00 | 1 | 5 | 0.11996 | 0.0000E+00 | ** | ** | ** | ** | |||
50000 | x5 | 1 | 2 | 0.06053 | 0.0000E+00 | 1 | 2 | 0.03772 | 0.0000E+00 | 1 | 2 | 0.03890 | 0.0000E+00 | 1 | 2 | 0.03026 | 0.0000E+00 | |||
50000 | x6 | 1 | 2 | 0.05694 | 0.0000E+00 | 1 | 2 | 0.03597 | 0.0000E+00 | 1 | 2 | 0.03897 | 0.0000E+00 | 1 | 2 | 0.03691 | 0.0000E+00 | |||
50000 | x7 | 1 | 2 | 0.06281 | 0.0000E+00 | 1 | 2 | 0.03922 | 0.0000E+00 | 1 | 2 | 0.03959 | 0.0000E+00 | 1 | 2 | 0.03842 | 0.0000E+00 | |||
50000 | x8 | 1 | 2 | 0.05664 | 0.0000E+00 | 1 | 2 | 0.03785 | 0.0000E+00 | 1 | 2 | 0.03866 | 0.0000E+00 | 1 | 2 | 0.04029 | 0.0000E+00 |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 44 | 271 | 0.62935 | 3.1455E-09 | 42 | 258 | 0.60676 | 6.9529E-09 | 33 | 161 | 0.45597 | 7.0484E-09 | ** | ** | ** | ** | |||
5000 | x2 | 39 | 243 | 0.63451 | 5.8143E-09 | 42 | 258 | 0.63349 | 6.8440E-09 | 49 | 253 | 0.65486 | 6.8393E-09 | ** | ** | ** | ** | |||
5000 | x3 | 40 | 252 | 0.60480 | 7.5147E-09 | 41 | 252 | 0.58345 | 9.1694E-09 | 31 | 147 | 0.42323 | 8.9989E-09 | ** | ** | ** | ** | |||
5000 | x4 | 37 | 233 | 0.57729 | 3.7953E-09 | 35 | 216 | 0.53482 | 9.0123E-09 | 40 | 194 | 0.51740 | 7.4457E-09 | ** | ** | ** | ** | |||
5000 | x5 | 33 | 202 | 0.46893 | 9.9461E-09 | 35 | 217 | 0.53483 | 8.7841E-09 | 42 | 204 | 0.52178 | 7.4199E-09 | ** | ** | ** | ** | |||
5000 | x6 | 34 | 212 | 0.52856 | 8.7562E-09 | 40 | 247 | 0.57437 | 6.6311E-09 | 64 | 358 | 0.89216 | 7.2966E-09 | ** | ** | ** | ** | |||
5000 | x7 | 43 | 267 | 0.70223 | 9.1513E-09 | 37 | 228 | 0.55987 | 7.0629E-09 | 33 | 160 | 0.43868 | 9.8882E-09 | ** | ** | ** | ** | |||
5000 | x8 | 39 | 244 | 0.62983 | 5.5424E-09 | 38 | 236 | 0.56374 | 9.7994E-09 | 39 | 212 | 0.51684 | 4.9792E-09 | ** | ** | ** | ** | |||
10000 | x1 | 46 | 283 | 1.24261 | 8.9039E-09 | 41 | 252 | 1.06589 | 8.7049E-09 | 43 | 201 | 0.99828 | 6.2921E-09 | ** | ** | ** | ** | |||
10000 | x2 | 43 | 270 | 1.20866 | 6.3134E-09 | 41 | 252 | 1.09452 | 8.5691E-09 | 33 | 125 | 0.65028 | 8.5659E-09 | ** | ** | ** | ** | |||
10000 | x3 | 35 | 213 | 0.98029 | 7.5116E-09 | 41 | 252 | 1.11311 | 7.5636E-09 | 38 | 200 | 0.90475 | 9.7816E-09 | ** | ** | ** | ** | |||
10000 | x4 | 41 | 256 | 1.13918 | 6.2659E-09 | 35 | 216 | 0.95719 | 7.4878E-09 | ** | ** | ** | ** | ** | ** | ** | ** | |||
10000 | x5 | 38 | 232 | 1.09266 | 4.3520E-09 | 35 | 217 | 0.95539 | 7.2962E-09 | 32 | 165 | 0.78884 | 6.7343E-09 | ** | ** | ** | ** | |||
10000 | x6 | 38 | 232 | 1.05984 | 8.2915E-09 | 39 | 241 | 1.02612 | 8.3641E-09 | 40 | 189 | 0.88094 | 8.8953E-09 | ** | ** | ** | ** | |||
10000 | x7 | 41 | 262 | 1.15504 | 6.3728E-09 | 32 | 200 | 0.91508 | 9.2095E-09 | 42 | 207 | 1.01358 | 9.6843E-09 | ** | ** | ** | ** | |||
10000 | x8 | 44 | 263 | 1.22024 | 4.4229E-09 | 45 | 278 | 1.23987 | 7.9323E-09 | ** | ** | ** | ** | ** | ** | ** | ** | |||
50000 | x1 | 51 | 316 | 6.68143 | 6.4806E-09 | 42 | 260 | 5.45556 | 7.9101E-09 | 38 | 187 | 4.12196 | 7.2817E-09 | ** | ** | ** | ** | |||
50000 | x2 | 48 | 301 | 6.33527 | 8.4813E-09 | 42 | 260 | 5.42795 | 7.8102E-09 | 40 | 181 | 4.31980 | 5.7514E-09 | ** | ** | ** | ** | |||
50000 | x3 | 36 | 218 | 4.66628 | 7.4951E-09 | 42 | 260 | 5.36750 | 7.0264E-09 | 44 | 190 | 4.36631 | 3.5019E-09 | ** | ** | ** | ** | |||
50000 | x4 | 33 | 206 | 4.39647 | 3.1500E-09 | 34 | 210 | 4.33667 | 7.4626E-09 | 34 | 143 | 3.36253 | 3.8370E-09 | ** | ** | ** | ** | |||
50000 | x5 | 36 | 226 | 4.71243 | 9.0560E-09 | 34 | 211 | 4.36821 | 7.2827E-09 | 32 | 132 | 3.13728 | 9.7006E-09 | ** | ** | ** | ** | |||
50000 | x6 | 38 | 235 | 4.97988 | 9.5093E-09 | 40 | 249 | 5.25738 | 8.0717E-09 | 36 | 164 | 3.76700 | 5.7396E-09 | ** | ** | ** | ** | |||
50000 | x7 | 44 | 282 | 5.86905 | 6.3230E-09 | 37 | 234 | 4.87686 | 6.5499E-09 | 40 | 200 | 4.41362 | 5.0952E-09 | ** | ** | ** | ** | |||
50000 | x8 | 37 | 231 | 4.86337 | 9.4485E-09 | 33 | 210 | 4.50616 | 9.9184E-09 | 36 | 138 | 3.29200 | 6.6412E-09 | ** | ** | ** | ** |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 44 | 271 | 0.62935 | 3.1455E-09 | 42 | 258 | 0.60676 | 6.9529E-09 | 33 | 161 | 0.45597 | 7.0484E-09 | ** | ** | ** | ** | |||
5000 | x2 | 39 | 243 | 0.63451 | 5.8143E-09 | 42 | 258 | 0.63349 | 6.8440E-09 | 49 | 253 | 0.65486 | 6.8393E-09 | ** | ** | ** | ** | |||
5000 | x3 | 40 | 252 | 0.60480 | 7.5147E-09 | 41 | 252 | 0.58345 | 9.1694E-09 | 31 | 147 | 0.42323 | 8.9989E-09 | ** | ** | ** | ** | |||
5000 | x4 | 37 | 233 | 0.57729 | 3.7953E-09 | 35 | 216 | 0.53482 | 9.0123E-09 | 40 | 194 | 0.51740 | 7.4457E-09 | ** | ** | ** | ** | |||
5000 | x5 | 33 | 202 | 0.46893 | 9.9461E-09 | 35 | 217 | 0.53483 | 8.7841E-09 | 42 | 204 | 0.52178 | 7.4199E-09 | ** | ** | ** | ** | |||
5000 | x6 | 34 | 212 | 0.52856 | 8.7562E-09 | 40 | 247 | 0.57437 | 6.6311E-09 | 64 | 358 | 0.89216 | 7.2966E-09 | ** | ** | ** | ** | |||
5000 | x7 | 43 | 267 | 0.70223 | 9.1513E-09 | 37 | 228 | 0.55987 | 7.0629E-09 | 33 | 160 | 0.43868 | 9.8882E-09 | ** | ** | ** | ** | |||
5000 | x8 | 39 | 244 | 0.62983 | 5.5424E-09 | 38 | 236 | 0.56374 | 9.7994E-09 | 39 | 212 | 0.51684 | 4.9792E-09 | ** | ** | ** | ** | |||
10000 | x1 | 46 | 283 | 1.24261 | 8.9039E-09 | 41 | 252 | 1.06589 | 8.7049E-09 | 43 | 201 | 0.99828 | 6.2921E-09 | ** | ** | ** | ** | |||
10000 | x2 | 43 | 270 | 1.20866 | 6.3134E-09 | 41 | 252 | 1.09452 | 8.5691E-09 | 33 | 125 | 0.65028 | 8.5659E-09 | ** | ** | ** | ** | |||
10000 | x3 | 35 | 213 | 0.98029 | 7.5116E-09 | 41 | 252 | 1.11311 | 7.5636E-09 | 38 | 200 | 0.90475 | 9.7816E-09 | ** | ** | ** | ** | |||
10000 | x4 | 41 | 256 | 1.13918 | 6.2659E-09 | 35 | 216 | 0.95719 | 7.4878E-09 | ** | ** | ** | ** | ** | ** | ** | ** | |||
10000 | x5 | 38 | 232 | 1.09266 | 4.3520E-09 | 35 | 217 | 0.95539 | 7.2962E-09 | 32 | 165 | 0.78884 | 6.7343E-09 | ** | ** | ** | ** | |||
10000 | x6 | 38 | 232 | 1.05984 | 8.2915E-09 | 39 | 241 | 1.02612 | 8.3641E-09 | 40 | 189 | 0.88094 | 8.8953E-09 | ** | ** | ** | ** | |||
10000 | x7 | 41 | 262 | 1.15504 | 6.3728E-09 | 32 | 200 | 0.91508 | 9.2095E-09 | 42 | 207 | 1.01358 | 9.6843E-09 | ** | ** | ** | ** | |||
10000 | x8 | 44 | 263 | 1.22024 | 4.4229E-09 | 45 | 278 | 1.23987 | 7.9323E-09 | ** | ** | ** | ** | ** | ** | ** | ** | |||
50000 | x1 | 51 | 316 | 6.68143 | 6.4806E-09 | 42 | 260 | 5.45556 | 7.9101E-09 | 38 | 187 | 4.12196 | 7.2817E-09 | ** | ** | ** | ** | |||
50000 | x2 | 48 | 301 | 6.33527 | 8.4813E-09 | 42 | 260 | 5.42795 | 7.8102E-09 | 40 | 181 | 4.31980 | 5.7514E-09 | ** | ** | ** | ** | |||
50000 | x3 | 36 | 218 | 4.66628 | 7.4951E-09 | 42 | 260 | 5.36750 | 7.0264E-09 | 44 | 190 | 4.36631 | 3.5019E-09 | ** | ** | ** | ** | |||
50000 | x4 | 33 | 206 | 4.39647 | 3.1500E-09 | 34 | 210 | 4.33667 | 7.4626E-09 | 34 | 143 | 3.36253 | 3.8370E-09 | ** | ** | ** | ** | |||
50000 | x5 | 36 | 226 | 4.71243 | 9.0560E-09 | 34 | 211 | 4.36821 | 7.2827E-09 | 32 | 132 | 3.13728 | 9.7006E-09 | ** | ** | ** | ** | |||
50000 | x6 | 38 | 235 | 4.97988 | 9.5093E-09 | 40 | 249 | 5.25738 | 8.0717E-09 | 36 | 164 | 3.76700 | 5.7396E-09 | ** | ** | ** | ** | |||
50000 | x7 | 44 | 282 | 5.86905 | 6.3230E-09 | 37 | 234 | 4.87686 | 6.5499E-09 | 40 | 200 | 4.41362 | 5.0952E-09 | ** | ** | ** | ** | |||
50000 | x8 | 37 | 231 | 4.86337 | 9.4485E-09 | 33 | 210 | 4.50616 | 9.9184E-09 | 36 | 138 | 3.29200 | 6.6412E-09 | ** | ** | ** | ** |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 4 | 6 | 0.01613 | 1.1694E-09 | 16 | 35 | 0.06067 | 4.1367E-09 | 11 | 25 | 0.04204 | 2.7254E-09 | 13 | 22 | 0.05005 | 2.5649E-09 | |||
5000 | x2 | 4 | 6 | 0.01681 | 8.3703E-09 | 16 | 35 | 0.06441 | 8.3035E-09 | 6 | 14 | 0.02475 | 3.7553E-09 | 15 | 25 | 0.05655 | 1.3159E-09 | |||
5000 | x3 | 3 | 5 | 0.01304 | 3.3286E-09 | 18 | 39 | 0.05937 | 4.7509E-09 | 12 | 28 | 0.04195 | 4.8432E-09 | 17 | 28 | 0.05855 | 5.2831E-09 | |||
5000 | x4 | 15 | 33 | 0.05422 | 1.7766E-09 | 20 | 43 | 0.06423 | 3.6850E-09 | 13 | 30 | 0.05059 | 2.4951E-09 | 21 | 35 | 0.09843 | 3.9220E-09 | |||
5000 | x5 | 10 | 23 | 0.05208 | 1.0831E-09 | 16 | 35 | 0.05671 | 5.9886E-09 | 15 | 36 | 0.06009 | 5.0128E-09 | 21 | 37 | 0.07153 | 3.9833E-09 | |||
5000 | x6 | 8 | 17 | 0.04271 | 6.9887E-09 | 20 | 44 | 0.06183 | 7.2667E-09 | 16 | 41 | 0.06403 | 4.8801E-09 | 22 | 42 | 0.09015 | 3.9830E-09 | |||
5000 | x7 | 20 | 44 | 0.06693 | 1.8089E-09 | 20 | 46 | 0.07138 | 9.6847E-09 | 15 | 43 | 0.05725 | 3.8385E-09 | 22 | 43 | 0.08100 | 3.9830E-09 | |||
5000 | x8 | 8 | 16 | 0.03136 | 2.2485E-09 | 20 | 46 | 0.06917 | 6.3318E-09 | 15 | 44 | 0.52479 | 4.4557E-09 | 22 | 44 | 0.08352 | 3.9830E-09 | |||
10000 | x1 | 4 | 6 | 0.02494 | 1.6538E-09 | 16 | 35 | 0.08973 | 5.8502E-09 | 11 | 25 | 0.06575 | 2.1388E-09 | 13 | 22 | 0.07581 | 3.6273E-09 | |||
10000 | x2 | 5 | 7 | 0.02770 | 1.0276E-10 | 17 | 37 | 0.08415 | 3.8974E-09 | 12 | 28 | 0.06498 | 3.1362E-09 | 15 | 25 | 0.12385 | 1.8610E-09 | |||
10000 | x3 | 3 | 5 | 0.02101 | 4.7073E-09 | 18 | 39 | 0.08491 | 6.7188E-09 | 11 | 26 | 0.07826 | 6.4560E-09 | 17 | 28 | 0.12292 | 7.4714E-09 | |||
10000 | x4 | 15 | 33 | 0.10815 | 2.5125E-09 | 20 | 43 | 0.09236 | 5.2114E-09 | 15 | 37 | 0.09462 | 2.7562E-09 | 21 | 35 | 0.13054 | 5.5465E-09 | |||
10000 | x5 | 10 | 23 | 0.06283 | 1.5317E-09 | 17 | 38 | 0.09884 | 9.9575E-09 | 16 | 40 | 0.21861 | 3.1439E-09 | 21 | 37 | 0.13807 | 5.6333E-09 | |||
10000 | x6 | 8 | 17 | 0.05651 | 9.8835E-09 | 21 | 48 | 0.11028 | 7.9275E-09 | 16 | 42 | 0.10622 | 4.2741E-09 | 22 | 42 | 0.13112 | 5.6328E-09 | |||
10000 | x7 | 20 | 44 | 0.10776 | 2.5582E-09 | 21 | 49 | 0.12883 | 4.5754E-09 | 16 | 46 | 0.08559 | 5.0752E-09 | 22 | 43 | 0.12979 | 5.6328E-09 | |||
10000 | x8 | 8 | 16 | 0.05015 | 3.1798E-09 | 20 | 47 | 0.11975 | 8.9545E-09 | 16 | 47 | 0.11307 | 5.1334E-09 | 22 | 44 | 0.12479 | 5.6328E-09 | |||
50000 | x1 | 4 | 6 | 0.09720 | 3.6981E-09 | 17 | 37 | 0.36221 | 4.3415E-09 | 12 | 28 | 0.27787 | 3.4805E-09 | 13 | 22 | 0.29020 | 8.1110E-09 | |||
50000 | x2 | 5 | 7 | 0.11296 | 2.2973E-10 | 17 | 37 | 0.32769 | 8.7148E-09 | 12 | 28 | 0.27745 | 5.2196E-09 | 15 | 25 | 0.48431 | 4.1613E-09 | |||
50000 | x3 | 4 | 7 | 0.09722 | 5.7871E-09 | 19 | 41 | 0.37649 | 4.9966E-09 | 13 | 31 | 0.30385 | 4.6998E-09 | 19 | 31 | 0.40698 | 2.0700E-09 | |||
50000 | x4 | 15 | 33 | 0.34967 | 5.6182E-09 | 22 | 49 | 0.42467 | 3.5662E-09 | 16 | 41 | 0.39497 | 5.2693E-09 | 23 | 38 | 0.48994 | 1.5367E-09 | |||
50000 | x5 | 10 | 23 | 0.25464 | 3.4249E-09 | 22 | 52 | 0.44383 | 8.0423E-09 | 18 | 50 | 0.44577 | 4.6654E-09 | 23 | 40 | 0.49968 | 1.5607E-09 | |||
50000 | x6 | 9 | 18 | 0.19377 | 6.5941E-10 | 23 | 55 | 0.46324 | 4.6940E-09 | 19 | 54 | 0.46182 | 5.3105E-09 | 24 | 45 | 0.53573 | 1.5606E-09 | |||
50000 | x7 | 20 | 44 | 0.43657 | 5.7203E-09 | 23 | 58 | 0.53040 | 9.1580E-09 | 18 | 57 | 0.47142 | 3.8366E-09 | 24 | 46 | 0.54006 | 1.5606E-09 | |||
50000 | x8 | 8 | 16 | 0.17111 | 7.1103E-09 | 23 | 58 | 0.49150 | 8.6064E-09 | 18 | 57 | 0.48898 | 3.4965E-09 | 24 | 47 | 0.56776 | 1.5606E-09 |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 4 | 6 | 0.01613 | 1.1694E-09 | 16 | 35 | 0.06067 | 4.1367E-09 | 11 | 25 | 0.04204 | 2.7254E-09 | 13 | 22 | 0.05005 | 2.5649E-09 | |||
5000 | x2 | 4 | 6 | 0.01681 | 8.3703E-09 | 16 | 35 | 0.06441 | 8.3035E-09 | 6 | 14 | 0.02475 | 3.7553E-09 | 15 | 25 | 0.05655 | 1.3159E-09 | |||
5000 | x3 | 3 | 5 | 0.01304 | 3.3286E-09 | 18 | 39 | 0.05937 | 4.7509E-09 | 12 | 28 | 0.04195 | 4.8432E-09 | 17 | 28 | 0.05855 | 5.2831E-09 | |||
5000 | x4 | 15 | 33 | 0.05422 | 1.7766E-09 | 20 | 43 | 0.06423 | 3.6850E-09 | 13 | 30 | 0.05059 | 2.4951E-09 | 21 | 35 | 0.09843 | 3.9220E-09 | |||
5000 | x5 | 10 | 23 | 0.05208 | 1.0831E-09 | 16 | 35 | 0.05671 | 5.9886E-09 | 15 | 36 | 0.06009 | 5.0128E-09 | 21 | 37 | 0.07153 | 3.9833E-09 | |||
5000 | x6 | 8 | 17 | 0.04271 | 6.9887E-09 | 20 | 44 | 0.06183 | 7.2667E-09 | 16 | 41 | 0.06403 | 4.8801E-09 | 22 | 42 | 0.09015 | 3.9830E-09 | |||
5000 | x7 | 20 | 44 | 0.06693 | 1.8089E-09 | 20 | 46 | 0.07138 | 9.6847E-09 | 15 | 43 | 0.05725 | 3.8385E-09 | 22 | 43 | 0.08100 | 3.9830E-09 | |||
5000 | x8 | 8 | 16 | 0.03136 | 2.2485E-09 | 20 | 46 | 0.06917 | 6.3318E-09 | 15 | 44 | 0.52479 | 4.4557E-09 | 22 | 44 | 0.08352 | 3.9830E-09 | |||
10000 | x1 | 4 | 6 | 0.02494 | 1.6538E-09 | 16 | 35 | 0.08973 | 5.8502E-09 | 11 | 25 | 0.06575 | 2.1388E-09 | 13 | 22 | 0.07581 | 3.6273E-09 | |||
10000 | x2 | 5 | 7 | 0.02770 | 1.0276E-10 | 17 | 37 | 0.08415 | 3.8974E-09 | 12 | 28 | 0.06498 | 3.1362E-09 | 15 | 25 | 0.12385 | 1.8610E-09 | |||
10000 | x3 | 3 | 5 | 0.02101 | 4.7073E-09 | 18 | 39 | 0.08491 | 6.7188E-09 | 11 | 26 | 0.07826 | 6.4560E-09 | 17 | 28 | 0.12292 | 7.4714E-09 | |||
10000 | x4 | 15 | 33 | 0.10815 | 2.5125E-09 | 20 | 43 | 0.09236 | 5.2114E-09 | 15 | 37 | 0.09462 | 2.7562E-09 | 21 | 35 | 0.13054 | 5.5465E-09 | |||
10000 | x5 | 10 | 23 | 0.06283 | 1.5317E-09 | 17 | 38 | 0.09884 | 9.9575E-09 | 16 | 40 | 0.21861 | 3.1439E-09 | 21 | 37 | 0.13807 | 5.6333E-09 | |||
10000 | x6 | 8 | 17 | 0.05651 | 9.8835E-09 | 21 | 48 | 0.11028 | 7.9275E-09 | 16 | 42 | 0.10622 | 4.2741E-09 | 22 | 42 | 0.13112 | 5.6328E-09 | |||
10000 | x7 | 20 | 44 | 0.10776 | 2.5582E-09 | 21 | 49 | 0.12883 | 4.5754E-09 | 16 | 46 | 0.08559 | 5.0752E-09 | 22 | 43 | 0.12979 | 5.6328E-09 | |||
10000 | x8 | 8 | 16 | 0.05015 | 3.1798E-09 | 20 | 47 | 0.11975 | 8.9545E-09 | 16 | 47 | 0.11307 | 5.1334E-09 | 22 | 44 | 0.12479 | 5.6328E-09 | |||
50000 | x1 | 4 | 6 | 0.09720 | 3.6981E-09 | 17 | 37 | 0.36221 | 4.3415E-09 | 12 | 28 | 0.27787 | 3.4805E-09 | 13 | 22 | 0.29020 | 8.1110E-09 | |||
50000 | x2 | 5 | 7 | 0.11296 | 2.2973E-10 | 17 | 37 | 0.32769 | 8.7148E-09 | 12 | 28 | 0.27745 | 5.2196E-09 | 15 | 25 | 0.48431 | 4.1613E-09 | |||
50000 | x3 | 4 | 7 | 0.09722 | 5.7871E-09 | 19 | 41 | 0.37649 | 4.9966E-09 | 13 | 31 | 0.30385 | 4.6998E-09 | 19 | 31 | 0.40698 | 2.0700E-09 | |||
50000 | x4 | 15 | 33 | 0.34967 | 5.6182E-09 | 22 | 49 | 0.42467 | 3.5662E-09 | 16 | 41 | 0.39497 | 5.2693E-09 | 23 | 38 | 0.48994 | 1.5367E-09 | |||
50000 | x5 | 10 | 23 | 0.25464 | 3.4249E-09 | 22 | 52 | 0.44383 | 8.0423E-09 | 18 | 50 | 0.44577 | 4.6654E-09 | 23 | 40 | 0.49968 | 1.5607E-09 | |||
50000 | x6 | 9 | 18 | 0.19377 | 6.5941E-10 | 23 | 55 | 0.46324 | 4.6940E-09 | 19 | 54 | 0.46182 | 5.3105E-09 | 24 | 45 | 0.53573 | 1.5606E-09 | |||
50000 | x7 | 20 | 44 | 0.43657 | 5.7203E-09 | 23 | 58 | 0.53040 | 9.1580E-09 | 18 | 57 | 0.47142 | 3.8366E-09 | 24 | 46 | 0.54006 | 1.5606E-09 | |||
50000 | x8 | 8 | 16 | 0.17111 | 7.1103E-09 | 23 | 58 | 0.49150 | 8.6064E-09 | 18 | 57 | 0.48898 | 3.4965E-09 | 24 | 47 | 0.56776 | 1.5606E-09 |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 13 | 29 | 0.08409 | 6.1206E-09 | 21 | 45 | 0.11835 | 4.5793E-09 | 13 | 34 | 0.07926 | 8.7285E-09 | 27 | 57 | 0.14177 | 9.2581E-09 | |||
5000 | x2 | 13 | 29 | 0.08607 | 6.0981E-09 | 21 | 45 | 0.11653 | 4.5624E-09 | 13 | 34 | 0.07905 | 8.6940E-09 | 27 | 57 | 0.14553 | 9.2256E-09 | |||
5000 | x3 | 13 | 29 | 0.08117 | 5.9183E-09 | 21 | 45 | 0.09188 | 4.4271E-09 | 13 | 34 | 0.09186 | 8.4192E-09 | 27 | 57 | 0.13343 | 8.9623E-09 | |||
5000 | x4 | 13 | 29 | 0.07941 | 4.4547E-09 | 20 | 43 | 0.14263 | 9.9982E-09 | 12 | 29 | 0.09527 | 8.3184E-09 | 27 | 57 | 0.14216 | 6.6834E-09 | |||
5000 | x5 | 13 | 29 | 0.07700 | 3.3263E-09 | 20 | 43 | 0.11080 | 7.4583E-09 | 15 | 38 | 0.09559 | 3.4919E-09 | 27 | 57 | 0.12148 | 4.9324E-09 | |||
5000 | x6 | 12 | 27 | 0.07471 | 8.0821E-09 | 20 | 43 | 0.12521 | 4.9185E-09 | 14 | 34 | 0.08074 | 3.5022E-09 | 26 | 55 | 0.12577 | 7.3575E-09 | |||
5000 | x7 | 12 | 27 | 0.11041 | 3.8935E-09 | 19 | 41 | 0.11220 | 7.1229E-09 | 13 | 31 | 0.07748 | 4.0165E-09 | 25 | 53 | 0.13185 | 8.0804E-09 | |||
5000 | x8 | 11 | 25 | 0.06216 | 4.7068E-09 | 18 | 39 | 0.10240 | 9.9853E-09 | 13 | 31 | 0.08459 | 3.3404E-09 | 24 | 51 | 0.51949 | 8.5601E-09 | |||
10000 | x1 | 13 | 30 | 0.15350 | 2.3785E-09 | 23 | 53 | 0.19978 | 5.1107E-09 | 15 | 46 | 0.16562 | 8.1229E-09 | 28 | 58 | 0.31646 | 0.0000E+00 | |||
10000 | x2 | 15 | 37 | 0.15897 | 5.1927E-09 | 23 | 53 | 0.19735 | 5.0918E-09 | 15 | 46 | 0.17351 | 8.0936E-09 | 28 | 58 | 0.24591 | 0.0000E+00 | |||
10000 | x3 | 19 | 54 | 0.23207 | 2.7569E-09 | 23 | 53 | 0.21008 | 4.9409E-09 | 15 | 46 | 0.15890 | 7.8592E-09 | 28 | 58 | 0.23659 | 0.0000E+00 | |||
10000 | x4 | 13 | 32 | 0.13566 | 2.2501E-09 | 21 | 45 | 0.18849 | 4.7069E-09 | 14 | 39 | 0.16351 | 6.5113E-09 | 27 | 57 | 0.37153 | 9.3333E-09 | |||
10000 | x5 | 14 | 35 | 0.13436 | 7.6581E-09 | 21 | 45 | 0.16255 | 3.5112E-09 | 13 | 34 | 0.12313 | 6.3921E-09 | 27 | 57 | 0.23985 | 6.9447E-09 | |||
10000 | x6 | 12 | 28 | 0.12876 | 7.1509E-09 | 20 | 43 | 0.18314 | 6.9563E-09 | 11 | 25 | 0.12049 | 8.3813E-09 | 27 | 56 | 0.25423 | 0.0000E+00 | |||
10000 | x7 | 9 | 18 | 0.08808 | 5.6775E-09 | 20 | 43 | 0.21754 | 3.3642E-09 | 12 | 29 | 0.13141 | 4.5477E-09 | 26 | 54 | 0.21101 | 0.0000E+00 | |||
10000 | x8 | 7 | 13 | 0.06663 | 5.1294E-09 | 19 | 41 | 0.16822 | 4.6958E-09 | 13 | 31 | 0.14696 | 4.3632E-09 | 25 | 52 | 0.23674 | 0.0000E+00 | |||
50000 | x1 | 8 | 14 | 0.31637 | 9.7835E-10 | 26 | 67 | 1.02269 | 9.0422E-09 | 23 | 107 | 1.49375 | 8.1128E-09 | 24 | 50 | 0.92306 | 0.0000E+00 | |||
50000 | x2 | 8 | 14 | 0.29982 | 9.7482E-10 | 26 | 67 | 1.06621 | 9.0088E-09 | 23 | 107 | 1.41950 | 8.0837E-09 | 24 | 50 | 0.92547 | 0.0000E+00 | |||
50000 | x3 | 8 | 14 | 0.29072 | 9.4607E-10 | 26 | 67 | 1.07177 | 8.7417E-09 | 23 | 104 | 1.38072 | 6.5311E-09 | 24 | 50 | 0.89133 | 0.0000E+00 | |||
50000 | x4 | 8 | 14 | 0.29903 | 7.1236E-10 | 25 | 63 | 1.00707 | 7.9619E-09 | 20 | 80 | 1.19303 | 6.3556E-09 | 24 | 50 | 0.94953 | 0.0000E+00 | |||
50000 | x5 | 8 | 14 | 0.29453 | 5.3210E-10 | 23 | 53 | 0.87334 | 6.1957E-09 | 17 | 58 | 0.90448 | 6.6277E-09 | 24 | 50 | 0.88540 | 0.0000E+00 | |||
50000 | x6 | 8 | 14 | 0.31612 | 3.5134E-10 | 22 | 49 | 0.86319 | 7.0213E-09 | 14 | 40 | 0.63377 | 7.7993E-09 | 22 | 46 | 0.86539 | 0.0000E+00 | |||
50000 | x7 | 8 | 14 | 0.28685 | 1.7015E-10 | 20 | 43 | 0.74746 | 7.5227E-09 | 15 | 38 | 0.65625 | 3.5221E-09 | 22 | 46 | 0.85031 | 0.0000E+00 | |||
50000 | x8 | 7 | 13 | 0.27290 | 5.4616E-09 | 20 | 43 | 0.74983 | 3.5066E-09 | 11 | 27 | 0.48111 | 6.0062E-09 | 22 | 46 | 0.85129 | 0.0000E+00 |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 13 | 29 | 0.08409 | 6.1206E-09 | 21 | 45 | 0.11835 | 4.5793E-09 | 13 | 34 | 0.07926 | 8.7285E-09 | 27 | 57 | 0.14177 | 9.2581E-09 | |||
5000 | x2 | 13 | 29 | 0.08607 | 6.0981E-09 | 21 | 45 | 0.11653 | 4.5624E-09 | 13 | 34 | 0.07905 | 8.6940E-09 | 27 | 57 | 0.14553 | 9.2256E-09 | |||
5000 | x3 | 13 | 29 | 0.08117 | 5.9183E-09 | 21 | 45 | 0.09188 | 4.4271E-09 | 13 | 34 | 0.09186 | 8.4192E-09 | 27 | 57 | 0.13343 | 8.9623E-09 | |||
5000 | x4 | 13 | 29 | 0.07941 | 4.4547E-09 | 20 | 43 | 0.14263 | 9.9982E-09 | 12 | 29 | 0.09527 | 8.3184E-09 | 27 | 57 | 0.14216 | 6.6834E-09 | |||
5000 | x5 | 13 | 29 | 0.07700 | 3.3263E-09 | 20 | 43 | 0.11080 | 7.4583E-09 | 15 | 38 | 0.09559 | 3.4919E-09 | 27 | 57 | 0.12148 | 4.9324E-09 | |||
5000 | x6 | 12 | 27 | 0.07471 | 8.0821E-09 | 20 | 43 | 0.12521 | 4.9185E-09 | 14 | 34 | 0.08074 | 3.5022E-09 | 26 | 55 | 0.12577 | 7.3575E-09 | |||
5000 | x7 | 12 | 27 | 0.11041 | 3.8935E-09 | 19 | 41 | 0.11220 | 7.1229E-09 | 13 | 31 | 0.07748 | 4.0165E-09 | 25 | 53 | 0.13185 | 8.0804E-09 | |||
5000 | x8 | 11 | 25 | 0.06216 | 4.7068E-09 | 18 | 39 | 0.10240 | 9.9853E-09 | 13 | 31 | 0.08459 | 3.3404E-09 | 24 | 51 | 0.51949 | 8.5601E-09 | |||
10000 | x1 | 13 | 30 | 0.15350 | 2.3785E-09 | 23 | 53 | 0.19978 | 5.1107E-09 | 15 | 46 | 0.16562 | 8.1229E-09 | 28 | 58 | 0.31646 | 0.0000E+00 | |||
10000 | x2 | 15 | 37 | 0.15897 | 5.1927E-09 | 23 | 53 | 0.19735 | 5.0918E-09 | 15 | 46 | 0.17351 | 8.0936E-09 | 28 | 58 | 0.24591 | 0.0000E+00 | |||
10000 | x3 | 19 | 54 | 0.23207 | 2.7569E-09 | 23 | 53 | 0.21008 | 4.9409E-09 | 15 | 46 | 0.15890 | 7.8592E-09 | 28 | 58 | 0.23659 | 0.0000E+00 | |||
10000 | x4 | 13 | 32 | 0.13566 | 2.2501E-09 | 21 | 45 | 0.18849 | 4.7069E-09 | 14 | 39 | 0.16351 | 6.5113E-09 | 27 | 57 | 0.37153 | 9.3333E-09 | |||
10000 | x5 | 14 | 35 | 0.13436 | 7.6581E-09 | 21 | 45 | 0.16255 | 3.5112E-09 | 13 | 34 | 0.12313 | 6.3921E-09 | 27 | 57 | 0.23985 | 6.9447E-09 | |||
10000 | x6 | 12 | 28 | 0.12876 | 7.1509E-09 | 20 | 43 | 0.18314 | 6.9563E-09 | 11 | 25 | 0.12049 | 8.3813E-09 | 27 | 56 | 0.25423 | 0.0000E+00 | |||
10000 | x7 | 9 | 18 | 0.08808 | 5.6775E-09 | 20 | 43 | 0.21754 | 3.3642E-09 | 12 | 29 | 0.13141 | 4.5477E-09 | 26 | 54 | 0.21101 | 0.0000E+00 | |||
10000 | x8 | 7 | 13 | 0.06663 | 5.1294E-09 | 19 | 41 | 0.16822 | 4.6958E-09 | 13 | 31 | 0.14696 | 4.3632E-09 | 25 | 52 | 0.23674 | 0.0000E+00 | |||
50000 | x1 | 8 | 14 | 0.31637 | 9.7835E-10 | 26 | 67 | 1.02269 | 9.0422E-09 | 23 | 107 | 1.49375 | 8.1128E-09 | 24 | 50 | 0.92306 | 0.0000E+00 | |||
50000 | x2 | 8 | 14 | 0.29982 | 9.7482E-10 | 26 | 67 | 1.06621 | 9.0088E-09 | 23 | 107 | 1.41950 | 8.0837E-09 | 24 | 50 | 0.92547 | 0.0000E+00 | |||
50000 | x3 | 8 | 14 | 0.29072 | 9.4607E-10 | 26 | 67 | 1.07177 | 8.7417E-09 | 23 | 104 | 1.38072 | 6.5311E-09 | 24 | 50 | 0.89133 | 0.0000E+00 | |||
50000 | x4 | 8 | 14 | 0.29903 | 7.1236E-10 | 25 | 63 | 1.00707 | 7.9619E-09 | 20 | 80 | 1.19303 | 6.3556E-09 | 24 | 50 | 0.94953 | 0.0000E+00 | |||
50000 | x5 | 8 | 14 | 0.29453 | 5.3210E-10 | 23 | 53 | 0.87334 | 6.1957E-09 | 17 | 58 | 0.90448 | 6.6277E-09 | 24 | 50 | 0.88540 | 0.0000E+00 | |||
50000 | x6 | 8 | 14 | 0.31612 | 3.5134E-10 | 22 | 49 | 0.86319 | 7.0213E-09 | 14 | 40 | 0.63377 | 7.7993E-09 | 22 | 46 | 0.86539 | 0.0000E+00 | |||
50000 | x7 | 8 | 14 | 0.28685 | 1.7015E-10 | 20 | 43 | 0.74746 | 7.5227E-09 | 15 | 38 | 0.65625 | 3.5221E-09 | 22 | 46 | 0.85031 | 0.0000E+00 | |||
50000 | x8 | 7 | 13 | 0.27290 | 5.4616E-09 | 20 | 43 | 0.74983 | 3.5066E-09 | 11 | 27 | 0.48111 | 6.0062E-09 | 22 | 46 | 0.85129 | 0.0000E+00 |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 11 | 29 | 0.05830 | 5.9634E-09 | 21 | 66 | 0.09121 | 4.9608E-09 | 12 | 33 | 0.05388 | 5.3440E-09 | 60 | 245 | 0.30692 | 9.2918E-09 | |||
5000 | x2 | 11 | 29 | 0.05493 | 4.3213E-09 | 21 | 66 | 0.07995 | 4.7837E-09 | 12 | 33 | 0.05358 | 5.8173E-09 | 60 | 245 | 0.29193 | 9.1558E-09 | |||
5000 | x3 | 10 | 27 | 0.04793 | 1.1728E-09 | 20 | 63 | 0.08563 | 9.6409E-09 | 12 | 33 | 0.05520 | 4.2467E-09 | 60 | 245 | 0.30544 | 7.9678E-09 | |||
5000 | x4 | 8 | 21 | 0.03816 | 8.8309E-09 | 6 | 15 | 0.02606 | 1.5409E-09 | 10 | 25 | 0.04814 | 5.5576E-09 | 59 | 241 | 0.27576 | 8.6175E-09 | |||
5000 | x5 | 17 | 52 | 0.08657 | 6.7905E-09 | 22 | 69 | 0.10643 | 3.8403E-09 | 12 | 32 | 0.06375 | 3.6002E-09 | 61 | 248 | 0.29183 | 8.0471E-09 | |||
5000 | x6 | 12 | 31 | 0.04854 | 6.6177E-09 | 22 | 68 | 0.11060 | 4.6406E-09 | 13 | 42 | 0.10346 | 5.9588E-09 | 62 | 250 | 0.29224 | 8.1876E-09 | |||
5000 | x7 | 13 | 36 | 0.05865 | 5.1067E-09 | 23 | 72 | 0.11025 | 5.6953E-09 | 11 | 31 | 0.05111 | 2.8649E-09 | 62 | 250 | 0.27411 | 7.6296E-09 | |||
5000 | x8 | 14 | 38 | 0.06893 | 9.5514E-10 | 7 | 18 | 0.03452 | 1.0412E-09 | 11 | 29 | 0.05033 | 7.4314E-09 | 62 | 250 | 0.31480 | 8.3682E-09 | |||
10000 | x1 | 11 | 29 | 0.12935 | 8.4335E-09 | 21 | 66 | 0.14482 | 7.0156E-09 | 13 | 37 | 0.09583 | 1.4459E-09 | 61 | 249 | 0.49287 | 9.5333E-09 | |||
10000 | x2 | 11 | 29 | 0.08446 | 6.1113E-09 | 21 | 66 | 0.18801 | 6.7652E-09 | 13 | 37 | 0.10481 | 1.7840E-09 | 61 | 249 | 0.50182 | 9.3937E-09 | |||
10000 | x3 | 10 | 27 | 0.08571 | 1.6586E-09 | 21 | 66 | 0.15276 | 4.9435E-09 | 12 | 33 | 0.10223 | 4.7426E-09 | 61 | 249 | 0.48216 | 8.1748E-09 | |||
10000 | x4 | 9 | 23 | 0.07085 | 1.8142E-09 | 6 | 15 | 0.05041 | 2.1791E-09 | 10 | 25 | 0.08289 | 9.5969E-09 | 60 | 245 | 0.46931 | 8.8414E-09 | |||
10000 | x5 | 17 | 52 | 0.14664 | 9.6032E-09 | 22 | 69 | 0.18159 | 5.4309E-09 | 11 | 28 | 0.08064 | 8.7915E-09 | 62 | 252 | 0.50543 | 8.2562E-09 | |||
10000 | x6 | 12 | 31 | 0.08264 | 9.3589E-09 | 23 | 73 | 0.15916 | 6.3474E-09 | 14 | 46 | 0.10846 | 1.7662E-09 | 63 | 254 | 0.51418 | 8.4004E-09 | |||
10000 | x7 | 13 | 36 | 0.12906 | 7.2220E-09 | 23 | 73 | 0.25665 | 8.5323E-09 | 14 | 43 | 0.10606 | 2.1715E-09 | 63 | 254 | 0.51744 | 7.8279E-09 | |||
10000 | x8 | 14 | 38 | 0.10402 | 1.3508E-09 | 7 | 18 | 0.07598 | 1.4725E-09 | 14 | 42 | 0.09957 | 2.1096E-09 | 63 | 254 | 0.49114 | 8.5857E-09 | |||
50000 | x1 | 12 | 31 | 0.33042 | 9.3840E-10 | 22 | 69 | 0.62427 | 5.6816E-09 | 14 | 41 | 0.42098 | 2.3754E-09 | 64 | 261 | 2.32850 | 8.1397E-09 | |||
50000 | x2 | 12 | 31 | 0.36379 | 5.6107E-10 | 22 | 69 | 0.62287 | 5.4788E-09 | 14 | 41 | 0.42743 | 2.1971E-09 | 64 | 261 | 2.27368 | 8.0206E-09 | |||
50000 | x3 | 10 | 27 | 0.29782 | 3.7088E-09 | 22 | 69 | 0.64410 | 4.0033E-09 | 13 | 39 | 0.41428 | 8.9237E-09 | 63 | 257 | 2.26461 | 9.6210E-09 | |||
50000 | x4 | 9 | 23 | 0.26084 | 4.0568E-09 | 6 | 15 | 0.17896 | 4.8726E-09 | 13 | 38 | 0.39586 | 3.2734E-09 | 63 | 257 | 2.21871 | 7.5490E-09 | |||
50000 | x5 | 18 | 54 | 0.54905 | 3.5244E-09 | 24 | 77 | 0.69938 | 4.1819E-09 | 17 | 62 | 0.58483 | 2.4241E-09 | 64 | 260 | 2.27889 | 9.7167E-09 | |||
50000 | x6 | 13 | 33 | 0.38900 | 1.9096E-09 | 24 | 77 | 0.74722 | 5.1440E-09 | 15 | 50 | 0.45349 | 5.4303E-09 | 65 | 262 | 2.28170 | 9.8864E-09 | |||
50000 | x7 | 14 | 38 | 0.38756 | 1.1869E-09 | 24 | 77 | 0.67827 | 6.9131E-09 | 14 | 39 | 0.40820 | 1.4432E-09 | 65 | 262 | 2.33294 | 9.2126E-09 | |||
50000 | x8 | 14 | 38 | 0.40306 | 3.0204E-09 | 24 | 77 | 0.69055 | 7.2256E-09 | 14 | 38 | 0.38383 | 1.4634E-09 | 66 | 266 | 2.30200 | 7.3306E-09 |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 11 | 29 | 0.05830 | 5.9634E-09 | 21 | 66 | 0.09121 | 4.9608E-09 | 12 | 33 | 0.05388 | 5.3440E-09 | 60 | 245 | 0.30692 | 9.2918E-09 | |||
5000 | x2 | 11 | 29 | 0.05493 | 4.3213E-09 | 21 | 66 | 0.07995 | 4.7837E-09 | 12 | 33 | 0.05358 | 5.8173E-09 | 60 | 245 | 0.29193 | 9.1558E-09 | |||
5000 | x3 | 10 | 27 | 0.04793 | 1.1728E-09 | 20 | 63 | 0.08563 | 9.6409E-09 | 12 | 33 | 0.05520 | 4.2467E-09 | 60 | 245 | 0.30544 | 7.9678E-09 | |||
5000 | x4 | 8 | 21 | 0.03816 | 8.8309E-09 | 6 | 15 | 0.02606 | 1.5409E-09 | 10 | 25 | 0.04814 | 5.5576E-09 | 59 | 241 | 0.27576 | 8.6175E-09 | |||
5000 | x5 | 17 | 52 | 0.08657 | 6.7905E-09 | 22 | 69 | 0.10643 | 3.8403E-09 | 12 | 32 | 0.06375 | 3.6002E-09 | 61 | 248 | 0.29183 | 8.0471E-09 | |||
5000 | x6 | 12 | 31 | 0.04854 | 6.6177E-09 | 22 | 68 | 0.11060 | 4.6406E-09 | 13 | 42 | 0.10346 | 5.9588E-09 | 62 | 250 | 0.29224 | 8.1876E-09 | |||
5000 | x7 | 13 | 36 | 0.05865 | 5.1067E-09 | 23 | 72 | 0.11025 | 5.6953E-09 | 11 | 31 | 0.05111 | 2.8649E-09 | 62 | 250 | 0.27411 | 7.6296E-09 | |||
5000 | x8 | 14 | 38 | 0.06893 | 9.5514E-10 | 7 | 18 | 0.03452 | 1.0412E-09 | 11 | 29 | 0.05033 | 7.4314E-09 | 62 | 250 | 0.31480 | 8.3682E-09 | |||
10000 | x1 | 11 | 29 | 0.12935 | 8.4335E-09 | 21 | 66 | 0.14482 | 7.0156E-09 | 13 | 37 | 0.09583 | 1.4459E-09 | 61 | 249 | 0.49287 | 9.5333E-09 | |||
10000 | x2 | 11 | 29 | 0.08446 | 6.1113E-09 | 21 | 66 | 0.18801 | 6.7652E-09 | 13 | 37 | 0.10481 | 1.7840E-09 | 61 | 249 | 0.50182 | 9.3937E-09 | |||
10000 | x3 | 10 | 27 | 0.08571 | 1.6586E-09 | 21 | 66 | 0.15276 | 4.9435E-09 | 12 | 33 | 0.10223 | 4.7426E-09 | 61 | 249 | 0.48216 | 8.1748E-09 | |||
10000 | x4 | 9 | 23 | 0.07085 | 1.8142E-09 | 6 | 15 | 0.05041 | 2.1791E-09 | 10 | 25 | 0.08289 | 9.5969E-09 | 60 | 245 | 0.46931 | 8.8414E-09 | |||
10000 | x5 | 17 | 52 | 0.14664 | 9.6032E-09 | 22 | 69 | 0.18159 | 5.4309E-09 | 11 | 28 | 0.08064 | 8.7915E-09 | 62 | 252 | 0.50543 | 8.2562E-09 | |||
10000 | x6 | 12 | 31 | 0.08264 | 9.3589E-09 | 23 | 73 | 0.15916 | 6.3474E-09 | 14 | 46 | 0.10846 | 1.7662E-09 | 63 | 254 | 0.51418 | 8.4004E-09 | |||
10000 | x7 | 13 | 36 | 0.12906 | 7.2220E-09 | 23 | 73 | 0.25665 | 8.5323E-09 | 14 | 43 | 0.10606 | 2.1715E-09 | 63 | 254 | 0.51744 | 7.8279E-09 | |||
10000 | x8 | 14 | 38 | 0.10402 | 1.3508E-09 | 7 | 18 | 0.07598 | 1.4725E-09 | 14 | 42 | 0.09957 | 2.1096E-09 | 63 | 254 | 0.49114 | 8.5857E-09 | |||
50000 | x1 | 12 | 31 | 0.33042 | 9.3840E-10 | 22 | 69 | 0.62427 | 5.6816E-09 | 14 | 41 | 0.42098 | 2.3754E-09 | 64 | 261 | 2.32850 | 8.1397E-09 | |||
50000 | x2 | 12 | 31 | 0.36379 | 5.6107E-10 | 22 | 69 | 0.62287 | 5.4788E-09 | 14 | 41 | 0.42743 | 2.1971E-09 | 64 | 261 | 2.27368 | 8.0206E-09 | |||
50000 | x3 | 10 | 27 | 0.29782 | 3.7088E-09 | 22 | 69 | 0.64410 | 4.0033E-09 | 13 | 39 | 0.41428 | 8.9237E-09 | 63 | 257 | 2.26461 | 9.6210E-09 | |||
50000 | x4 | 9 | 23 | 0.26084 | 4.0568E-09 | 6 | 15 | 0.17896 | 4.8726E-09 | 13 | 38 | 0.39586 | 3.2734E-09 | 63 | 257 | 2.21871 | 7.5490E-09 | |||
50000 | x5 | 18 | 54 | 0.54905 | 3.5244E-09 | 24 | 77 | 0.69938 | 4.1819E-09 | 17 | 62 | 0.58483 | 2.4241E-09 | 64 | 260 | 2.27889 | 9.7167E-09 | |||
50000 | x6 | 13 | 33 | 0.38900 | 1.9096E-09 | 24 | 77 | 0.74722 | 5.1440E-09 | 15 | 50 | 0.45349 | 5.4303E-09 | 65 | 262 | 2.28170 | 9.8864E-09 | |||
50000 | x7 | 14 | 38 | 0.38756 | 1.1869E-09 | 24 | 77 | 0.67827 | 6.9131E-09 | 14 | 39 | 0.40820 | 1.4432E-09 | 65 | 262 | 2.33294 | 9.2126E-09 | |||
50000 | x8 | 14 | 38 | 0.40306 | 3.0204E-09 | 24 | 77 | 0.69055 | 7.2256E-09 | 14 | 38 | 0.38383 | 1.4634E-09 | 66 | 266 | 2.30200 | 7.3306E-09 |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 16 | 59 | 0.09432 | 1.3050E-09 | 30 | 124 | 0.14592 | 7.0705E-09 | 10 | 32 | 0.04996 | 7.5384E-09 | 57 | 349 | 0.32182 | 9.4550E-09 | |||
5000 | x2 | 14 | 53 | 0.07568 | 4.0067E-09 | 30 | 124 | 0.13148 | 6.9353E-09 | 10 | 30 | 0.04617 | 9.1316E-09 | 57 | 349 | 0.35728 | 9.3912E-09 | |||
5000 | x3 | 16 | 60 | 0.08765 | 6.4133E-09 | 30 | 124 | 0.13896 | 5.8827E-09 | 9 | 30 | 0.03916 | 7.4550E-09 | 57 | 349 | 0.30529 | 8.7821E-09 | |||
5000 | x4 | 16 | 62 | 0.07775 | 5.5391E-09 | 11 | 37 | 0.06037 | 1.8485E-09 | 9 | 29 | 0.04321 | 4.7455E-09 | 53 | 325 | 0.31769 | 7.4711E-09 | |||
5000 | x5 | 15 | 57 | 0.07999 | 9.8573E-09 | 12 | 40 | 0.05478 | 9.3263E-09 | 11 | 37 | 0.05279 | 5.2468E-09 | 57 | 346 | 0.31532 | 7.5276E-09 | |||
5000 | x6 | 15 | 58 | 0.07809 | 7.8166E-09 | 13 | 43 | 0.06090 | 2.5833E-09 | ** | ** | ** | ** | 58 | 349 | 0.29898 | 8.0592E-09 | |||
5000 | x7 | 16 | 59 | 0.08286 | 1.3795E-09 | 14 | 44 | 0.07650 | 3.3787E-09 | ** | ** | ** | ** | 56 | 333 | 0.32301 | 7.5313E-09 | |||
5000 | x8 | 12 | 42 | 0.06033 | 2.4066E-10 | 14 | 43 | 0.06044 | 6.0314E-09 | ** | ** | ** | ** | 54 | 321 | 0.29418 | 8.5637E-09 | |||
10000 | x1 | 16 | 59 | 0.14692 | 1.8456E-09 | 30 | 124 | 0.26347 | 9.9993E-09 | 11 | 33 | 0.06356 | 7.5740E-09 | 58 | 355 | 0.54602 | 9.3986E-09 | |||
10000 | x2 | 14 | 53 | 0.10996 | 5.6664E-09 | 30 | 124 | 0.23092 | 9.8079E-09 | 11 | 34 | 0.07902 | 4.5397E-11 | 58 | 355 | 0.55024 | 9.3352E-09 | |||
10000 | x3 | 16 | 60 | 0.13400 | 9.0698E-09 | 30 | 124 | 0.21597 | 8.3194E-09 | 13 | 43 | 0.10110 | 9.3470E-09 | 58 | 355 | 0.53853 | 8.7297E-09 | |||
10000 | x4 | 16 | 62 | 0.13363 | 7.8334E-09 | 11 | 37 | 0.30166 | 2.6142E-09 | 6 | 19 | 0.04657 | 4.5079E-10 | 54 | 331 | 0.52338 | 7.4265E-09 | |||
10000 | x5 | 16 | 61 | 0.12671 | 4.8938E-09 | 13 | 43 | 0.07998 | 1.9679E-09 | 11 | 39 | 0.08054 | 2.4455E-09 | 58 | 352 | 0.52326 | 7.4827E-09 | |||
10000 | x6 | 16 | 62 | 0.12887 | 5.9649E-09 | 13 | 43 | 0.09948 | 3.6534E-09 | ** | ** | ** | ** | 59 | 355 | 0.61184 | 8.0112E-09 | |||
10000 | x7 | 16 | 59 | 0.14343 | 1.9510E-09 | 14 | 44 | 0.07941 | 4.7783E-09 | ** | ** | ** | ** | 57 | 339 | 0.51324 | 7.4864E-09 | |||
10000 | x8 | 12 | 42 | 0.09692 | 3.4034E-10 | 14 | 43 | 0.09317 | 8.5297E-09 | 167 | 1820 | 2.60568 | 4.7429E-11 | 55 | 327 | 0.52918 | 8.5127E-09 | |||
50000 | x1 | 16 | 59 | 0.52241 | 4.1268E-09 | 32 | 132 | 0.95785 | 4.9313E-09 | 14 | 54 | 0.46701 | 1.1179E-09 | 61 | 373 | 2.61151 | 7.2981E-09 | |||
50000 | x2 | 15 | 56 | 0.46085 | 5.5395E-09 | 32 | 132 | 0.98458 | 4.8369E-09 | 16 | 60 | 0.51123 | 4.0239E-10 | 61 | 373 | 2.58425 | 7.2489E-09 | |||
50000 | x3 | 17 | 64 | 0.56293 | 7.8990E-09 | 31 | 128 | 0.97264 | 8.7364E-09 | 16 | 58 | 0.52341 | 3.8080E-09 | 60 | 367 | 2.53142 | 9.6440E-09 | |||
50000 | x4 | 17 | 65 | 0.52033 | 1.7365E-09 | 11 | 37 | 0.33492 | 5.8455E-09 | 10 | 32 | 0.30108 | 3.4982E-09 | 56 | 343 | 2.30189 | 8.2044E-09 | |||
50000 | x5 | 17 | 64 | 0.56208 | 1.1172E-09 | 13 | 43 | 0.40677 | 4.4003E-09 | 87 | 897 | 5.90688 | 5.5572E-09 | 60 | 364 | 2.46086 | 8.2665E-09 | |||
50000 | x6 | 17 | 66 | 0.57559 | 4.9142E-09 | 13 | 43 | 0.38142 | 8.1692E-09 | 61 | 577 | 4.09402 | 3.9378E-09 | 61 | 367 | 2.51340 | 8.8502E-09 | |||
50000 | x7 | 16 | 59 | 0.51799 | 4.3625E-09 | 17 | 54 | 0.49638 | 1.9299E-09 | 66 | 643 | 4.51278 | 7.7185E-09 | 59 | 351 | 2.42242 | 8.2705E-09 | |||
50000 | x8 | 12 | 42 | 0.40991 | 7.6102E-10 | 35 | 137 | 1.04612 | 6.9307E-09 | 185 | 1959 | 12.83235 | 7.1829E-09 | 57 | 339 | 2.30068 | 9.4043E-09 |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 16 | 59 | 0.09432 | 1.3050E-09 | 30 | 124 | 0.14592 | 7.0705E-09 | 10 | 32 | 0.04996 | 7.5384E-09 | 57 | 349 | 0.32182 | 9.4550E-09 | |||
5000 | x2 | 14 | 53 | 0.07568 | 4.0067E-09 | 30 | 124 | 0.13148 | 6.9353E-09 | 10 | 30 | 0.04617 | 9.1316E-09 | 57 | 349 | 0.35728 | 9.3912E-09 | |||
5000 | x3 | 16 | 60 | 0.08765 | 6.4133E-09 | 30 | 124 | 0.13896 | 5.8827E-09 | 9 | 30 | 0.03916 | 7.4550E-09 | 57 | 349 | 0.30529 | 8.7821E-09 | |||
5000 | x4 | 16 | 62 | 0.07775 | 5.5391E-09 | 11 | 37 | 0.06037 | 1.8485E-09 | 9 | 29 | 0.04321 | 4.7455E-09 | 53 | 325 | 0.31769 | 7.4711E-09 | |||
5000 | x5 | 15 | 57 | 0.07999 | 9.8573E-09 | 12 | 40 | 0.05478 | 9.3263E-09 | 11 | 37 | 0.05279 | 5.2468E-09 | 57 | 346 | 0.31532 | 7.5276E-09 | |||
5000 | x6 | 15 | 58 | 0.07809 | 7.8166E-09 | 13 | 43 | 0.06090 | 2.5833E-09 | ** | ** | ** | ** | 58 | 349 | 0.29898 | 8.0592E-09 | |||
5000 | x7 | 16 | 59 | 0.08286 | 1.3795E-09 | 14 | 44 | 0.07650 | 3.3787E-09 | ** | ** | ** | ** | 56 | 333 | 0.32301 | 7.5313E-09 | |||
5000 | x8 | 12 | 42 | 0.06033 | 2.4066E-10 | 14 | 43 | 0.06044 | 6.0314E-09 | ** | ** | ** | ** | 54 | 321 | 0.29418 | 8.5637E-09 | |||
10000 | x1 | 16 | 59 | 0.14692 | 1.8456E-09 | 30 | 124 | 0.26347 | 9.9993E-09 | 11 | 33 | 0.06356 | 7.5740E-09 | 58 | 355 | 0.54602 | 9.3986E-09 | |||
10000 | x2 | 14 | 53 | 0.10996 | 5.6664E-09 | 30 | 124 | 0.23092 | 9.8079E-09 | 11 | 34 | 0.07902 | 4.5397E-11 | 58 | 355 | 0.55024 | 9.3352E-09 | |||
10000 | x3 | 16 | 60 | 0.13400 | 9.0698E-09 | 30 | 124 | 0.21597 | 8.3194E-09 | 13 | 43 | 0.10110 | 9.3470E-09 | 58 | 355 | 0.53853 | 8.7297E-09 | |||
10000 | x4 | 16 | 62 | 0.13363 | 7.8334E-09 | 11 | 37 | 0.30166 | 2.6142E-09 | 6 | 19 | 0.04657 | 4.5079E-10 | 54 | 331 | 0.52338 | 7.4265E-09 | |||
10000 | x5 | 16 | 61 | 0.12671 | 4.8938E-09 | 13 | 43 | 0.07998 | 1.9679E-09 | 11 | 39 | 0.08054 | 2.4455E-09 | 58 | 352 | 0.52326 | 7.4827E-09 | |||
10000 | x6 | 16 | 62 | 0.12887 | 5.9649E-09 | 13 | 43 | 0.09948 | 3.6534E-09 | ** | ** | ** | ** | 59 | 355 | 0.61184 | 8.0112E-09 | |||
10000 | x7 | 16 | 59 | 0.14343 | 1.9510E-09 | 14 | 44 | 0.07941 | 4.7783E-09 | ** | ** | ** | ** | 57 | 339 | 0.51324 | 7.4864E-09 | |||
10000 | x8 | 12 | 42 | 0.09692 | 3.4034E-10 | 14 | 43 | 0.09317 | 8.5297E-09 | 167 | 1820 | 2.60568 | 4.7429E-11 | 55 | 327 | 0.52918 | 8.5127E-09 | |||
50000 | x1 | 16 | 59 | 0.52241 | 4.1268E-09 | 32 | 132 | 0.95785 | 4.9313E-09 | 14 | 54 | 0.46701 | 1.1179E-09 | 61 | 373 | 2.61151 | 7.2981E-09 | |||
50000 | x2 | 15 | 56 | 0.46085 | 5.5395E-09 | 32 | 132 | 0.98458 | 4.8369E-09 | 16 | 60 | 0.51123 | 4.0239E-10 | 61 | 373 | 2.58425 | 7.2489E-09 | |||
50000 | x3 | 17 | 64 | 0.56293 | 7.8990E-09 | 31 | 128 | 0.97264 | 8.7364E-09 | 16 | 58 | 0.52341 | 3.8080E-09 | 60 | 367 | 2.53142 | 9.6440E-09 | |||
50000 | x4 | 17 | 65 | 0.52033 | 1.7365E-09 | 11 | 37 | 0.33492 | 5.8455E-09 | 10 | 32 | 0.30108 | 3.4982E-09 | 56 | 343 | 2.30189 | 8.2044E-09 | |||
50000 | x5 | 17 | 64 | 0.56208 | 1.1172E-09 | 13 | 43 | 0.40677 | 4.4003E-09 | 87 | 897 | 5.90688 | 5.5572E-09 | 60 | 364 | 2.46086 | 8.2665E-09 | |||
50000 | x6 | 17 | 66 | 0.57559 | 4.9142E-09 | 13 | 43 | 0.38142 | 8.1692E-09 | 61 | 577 | 4.09402 | 3.9378E-09 | 61 | 367 | 2.51340 | 8.8502E-09 | |||
50000 | x7 | 16 | 59 | 0.51799 | 4.3625E-09 | 17 | 54 | 0.49638 | 1.9299E-09 | 66 | 643 | 4.51278 | 7.7185E-09 | 59 | 351 | 2.42242 | 8.2705E-09 | |||
50000 | x8 | 12 | 42 | 0.40991 | 7.6102E-10 | 35 | 137 | 1.04612 | 6.9307E-09 | 185 | 1959 | 12.83235 | 7.1829E-09 | 57 | 339 | 2.30068 | 9.4043E-09 |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 14 | 105 | 0.16757 | 0.0000E+00 | ** | ** | ** | ** | 8 | 76 | 0.08422 | 0.0000E+00 | 3 | 19 | 0.03360 | 0.0000E+00 | |||
5000 | x2 | 14 | 102 | 0.14631 | 0.0000E+00 | ** | ** | ** | ** | 8 | 76 | 0.10084 | 0.0000E+00 | 5 | 32 | 0.05756 | 0.0000E+00 | |||
5000 | x3 | 14 | 96 | 0.13992 | 0.0000E+00 | 4 | 34 | 0.03438 | 0.0000E+00 | 15 | 141 | 0.16698 | 0.0000E+00 | 4 | 20 | 0.06854 | 0.0000E+00 | |||
5000 | x4 | 17 | 126 | 0.17229 | 0.0000E+00 | 5 | 44 | 0.06671 | 0.0000E+00 | 16 | 90 | 0.14892 | 0.0000E+00 | 2 | 16 | 0.03029 | 0.0000E+00 | |||
5000 | x5 | 7 | 55 | 0.08252 | 0.0000E+00 | 6 | 44 | 0.07206 | 0.0000E+00 | 22 | 125 | 0.19471 | 0.0000E+00 | 3 | 30 | 0.06496 | 0.0000E+00 | |||
5000 | x6 | 4 | 30 | 0.04918 | 0.0000E+00 | 3 | 19 | 0.04112 | 0.0000E+00 | 13 | 95 | 0.14016 | 0.0000E+00 | 2 | 19 | 0.03237 | 0.0000E+00 | |||
5000 | x7 | 4 | 30 | 0.05837 | 0.0000E+00 | 5 | 36 | 0.06107 | 0.0000E+00 | 19 | 111 | 0.18132 | 0.0000E+00 | 2 | 20 | 0.04827 | 0.0000E+00 | |||
5000 | x8 | 6 | 55 | 0.08952 | 0.0000E+00 | 4 | 24 | 0.06101 | 0.0000E+00 | 68 | 499 | 0.65635 | 0.0000E+00 | 3 | 22 | 0.03871 | 0.0000E+00 | |||
10000 | x1 | 10 | 73 | 1.18135 | 0.0000E+00 | 5 | 35 | 0.11482 | 0.0000E+00 | 8 | 76 | 0.16320 | 0.0000E+00 | 3 | 19 | 0.05802 | 0.0000E+00 | |||
10000 | x2 | 11 | 75 | 0.20685 | 0.0000E+00 | 212 | 1703 | 3.57595 | 0.0000E+00 | 8 | 76 | 0.20896 | 0.0000E+00 | 3 | 19 | 0.06237 | 0.0000E+00 | |||
10000 | x3 | 14 | 94 | 0.24852 | 0.0000E+00 | 5 | 37 | 0.11556 | 0.0000E+00 | 5 | 51 | 0.13497 | 0.0000E+00 | 4 | 20 | 0.06374 | 0.0000E+00 | |||
10000 | x4 | 10 | 74 | 0.20559 | 0.0000E+00 | 3 | 20 | 0.05981 | 0.0000E+00 | 26 | 243 | 0.57624 | 0.0000E+00 | 2 | 16 | 0.05057 | 0.0000E+00 | |||
10000 | x5 | 4 | 35 | 0.09897 | 0.0000E+00 | 5 | 31 | 0.09720 | 0.0000E+00 | 31 | 267 | 0.65314 | 0.0000E+00 | 3 | 30 | 0.08397 | 0.0000E+00 | |||
10000 | x6 | 3 | 18 | 0.05165 | 0.0000E+00 | 5 | 34 | 0.10333 | 0.0000E+00 | 12 | 108 | 0.25737 | 0.0000E+00 | 2 | 19 | 0.05356 | 0.0000E+00 | |||
10000 | x7 | 5 | 42 | 0.13123 | 0.0000E+00 | 4 | 23 | 0.07361 | 0.0000E+00 | 33 | 288 | 0.65692 | 0.0000E+00 | 2 | 20 | 0.05280 | 0.0000E+00 | |||
10000 | x8 | 4 | 25 | 0.07246 | 0.0000E+00 | 4 | 23 | 0.08236 | 0.0000E+00 | 7 | 64 | 0.17944 | 0.0000E+00 | 3 | 22 | 0.06539 | 0.0000E+00 | |||
50000 | x1 | 10 | 72 | 0.86301 | 0.0000E+00 | 7 | 42 | 0.49996 | 0.0000E+00 | 8 | 76 | 0.82304 | 0.0000E+00 | 3 | 19 | 0.24206 | 0.0000E+00 | |||
50000 | x2 | 9 | 71 | 0.85537 | 0.0000E+00 | 7 | 41 | 0.49430 | 0.0000E+00 | 8 | 76 | 0.85630 | 0.0000E+00 | 3 | 19 | 0.24635 | 0.0000E+00 | |||
50000 | x3 | 10 | 71 | 0.82141 | 0.0000E+00 | 7 | 39 | 0.46821 | 0.0000E+00 | 4 | 28 | 0.35046 | 0.0000E+00 | 3 | 19 | 0.23377 | 0.0000E+00 | |||
50000 | x4 | 8 | 51 | 0.64090 | 0.0000E+00 | ** | ** | ** | ** | 7 | 60 | 0.69240 | 0.0000E+00 | 2 | 16 | 0.16730 | 0.0000E+00 | |||
50000 | x5 | 3 | 24 | 0.29724 | 0.0000E+00 | 7 | 38 | 0.40553 | 0.0000E+00 | 9 | 69 | 0.73666 | 0.0000E+00 | 4 | 31 | 0.32924 | 0.0000E+00 | |||
50000 | x6 | 3 | 18 | 0.25253 | 0.0000E+00 | 7 | 40 | 0.47899 | 0.0000E+00 | 10 | 73 | 0.88118 | 0.0000E+00 | 2 | 19 | 0.20408 | 0.0000E+00 | |||
50000 | x7 | 3 | 18 | 0.22632 | 0.0000E+00 | ** | ** | ** | ** | 8 | 64 | 0.74632 | 0.0000E+00 | 2 | 20 | 0.23963 | 0.0000E+00 | |||
50000 | x8 | 4 | 24 | 0.30785 | 0.0000E+00 | 6 | 32 | 0.33168 | 0.0000E+00 | 36 | 246 | 2.80129 | 0.0000E+00 | 3 | 22 | 0.27244 | 0.0000E+00 |
Nvars | IGuess | MDDYM | PDYM | MDY | MFR | |||||||||||||||
Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | Niter | Nfev | Cpt | Norm | |||||
5000 | x1 | 14 | 105 | 0.16757 | 0.0000E+00 | ** | ** | ** | ** | 8 | 76 | 0.08422 | 0.0000E+00 | 3 | 19 | 0.03360 | 0.0000E+00 | |||
5000 | x2 | 14 | 102 | 0.14631 | 0.0000E+00 | ** | ** | ** | ** | 8 | 76 | 0.10084 | 0.0000E+00 | 5 | 32 | 0.05756 | 0.0000E+00 | |||
5000 | x3 | 14 | 96 | 0.13992 | 0.0000E+00 | 4 | 34 | 0.03438 | 0.0000E+00 | 15 | 141 | 0.16698 | 0.0000E+00 | 4 | 20 | 0.06854 | 0.0000E+00 | |||
5000 | x4 | 17 | 126 | 0.17229 | 0.0000E+00 | 5 | 44 | 0.06671 | 0.0000E+00 | 16 | 90 | 0.14892 | 0.0000E+00 | 2 | 16 | 0.03029 | 0.0000E+00 | |||
5000 | x5 | 7 | 55 | 0.08252 | 0.0000E+00 | 6 | 44 | 0.07206 | 0.0000E+00 | 22 | 125 | 0.19471 | 0.0000E+00 | 3 | 30 | 0.06496 | 0.0000E+00 | |||
5000 | x6 | 4 | 30 | 0.04918 | 0.0000E+00 | 3 | 19 | 0.04112 | 0.0000E+00 | 13 | 95 | 0.14016 | 0.0000E+00 | 2 | 19 | 0.03237 | 0.0000E+00 | |||
5000 | x7 | 4 | 30 | 0.05837 | 0.0000E+00 | 5 | 36 | 0.06107 | 0.0000E+00 | 19 | 111 | 0.18132 | 0.0000E+00 | 2 | 20 | 0.04827 | 0.0000E+00 | |||
5000 | x8 | 6 | 55 | 0.08952 | 0.0000E+00 | 4 | 24 | 0.06101 | 0.0000E+00 | 68 | 499 | 0.65635 | 0.0000E+00 | 3 | 22 | 0.03871 | 0.0000E+00 | |||
10000 | x1 | 10 | 73 | 1.18135 | 0.0000E+00 | 5 | 35 | 0.11482 | 0.0000E+00 | 8 | 76 | 0.16320 | 0.0000E+00 | 3 | 19 | 0.05802 | 0.0000E+00 | |||
10000 | x2 | 11 | 75 | 0.20685 | 0.0000E+00 | 212 | 1703 | 3.57595 | 0.0000E+00 | 8 | 76 | 0.20896 | 0.0000E+00 | 3 | 19 | 0.06237 | 0.0000E+00 | |||
10000 | x3 | 14 | 94 | 0.24852 | 0.0000E+00 | 5 | 37 | 0.11556 | 0.0000E+00 | 5 | 51 | 0.13497 | 0.0000E+00 | 4 | 20 | 0.06374 | 0.0000E+00 | |||
10000 | x4 | 10 | 74 | 0.20559 | 0.0000E+00 | 3 | 20 | 0.05981 | 0.0000E+00 | 26 | 243 | 0.57624 | 0.0000E+00 | 2 | 16 | 0.05057 | 0.0000E+00 | |||
10000 | x5 | 4 | 35 | 0.09897 | 0.0000E+00 | 5 | 31 | 0.09720 | 0.0000E+00 | 31 | 267 | 0.65314 | 0.0000E+00 | 3 | 30 | 0.08397 | 0.0000E+00 | |||
10000 | x6 | 3 | 18 | 0.05165 | 0.0000E+00 | 5 | 34 | 0.10333 | 0.0000E+00 | 12 | 108 | 0.25737 | 0.0000E+00 | 2 | 19 | 0.05356 | 0.0000E+00 | |||
10000 | x7 | 5 | 42 | 0.13123 | 0.0000E+00 | 4 | 23 | 0.07361 | 0.0000E+00 | 33 | 288 | 0.65692 | 0.0000E+00 | 2 | 20 | 0.05280 | 0.0000E+00 | |||
10000 | x8 | 4 | 25 | 0.07246 | 0.0000E+00 | 4 | 23 | 0.08236 | 0.0000E+00 | 7 | 64 | 0.17944 | 0.0000E+00 | 3 | 22 | 0.06539 | 0.0000E+00 | |||
50000 | x1 | 10 | 72 | 0.86301 | 0.0000E+00 | 7 | 42 | 0.49996 | 0.0000E+00 | 8 | 76 | 0.82304 | 0.0000E+00 | 3 | 19 | 0.24206 | 0.0000E+00 | |||
50000 | x2 | 9 | 71 | 0.85537 | 0.0000E+00 | 7 | 41 | 0.49430 | 0.0000E+00 | 8 | 76 | 0.85630 | 0.0000E+00 | 3 | 19 | 0.24635 | 0.0000E+00 | |||
50000 | x3 | 10 | 71 | 0.82141 | 0.0000E+00 | 7 | 39 | 0.46821 | 0.0000E+00 | 4 | 28 | 0.35046 | 0.0000E+00 | 3 | 19 | 0.23377 | 0.0000E+00 | |||
50000 | x4 | 8 | 51 | 0.64090 | 0.0000E+00 | ** | ** | ** | ** | 7 | 60 | 0.69240 | 0.0000E+00 | 2 | 16 | 0.16730 | 0.0000E+00 | |||
50000 | x5 | 3 | 24 | 0.29724 | 0.0000E+00 | 7 | 38 | 0.40553 | 0.0000E+00 | 9 | 69 | 0.73666 | 0.0000E+00 | 4 | 31 | 0.32924 | 0.0000E+00 | |||
50000 | x6 | 3 | 18 | 0.25253 | 0.0000E+00 | 7 | 40 | 0.47899 | 0.0000E+00 | 10 | 73 | 0.88118 | 0.0000E+00 | 2 | 19 | 0.20408 | 0.0000E+00 | |||
50000 | x7 | 3 | 18 | 0.22632 | 0.0000E+00 | ** | ** | ** | ** | 8 | 64 | 0.74632 | 0.0000E+00 | 2 | 20 | 0.23963 | 0.0000E+00 | |||
50000 | x8 | 4 | 24 | 0.30785 | 0.0000E+00 | 6 | 32 | 0.33168 | 0.0000E+00 | 36 | 246 | 2.80129 | 0.0000E+00 | 3 | 22 | 0.27244 | 0.0000E+00 |
Method | Niter | Percentage | fev | Percentage | Ptime | Percentage | Fails |
MDDYM | 83 | 43.22% | 91 | 47.40% | 81 | 40.19% | - |
PDYM | 19 | 9.90% | 14 | 7.29% | 30 | 15.63% | 4 |
MDY | 36 | 18.75% | 40 | 20.83% | 55 | 28.65% | 7 |
MFR | 23 | 11.98% | 20 | 10.42% | 26 | 13.53% | 27 |
Undecided | 31 | 16.15% | 27 | 14.06% | - | - | - |
Method | Niter | Percentage | fev | Percentage | Ptime | Percentage | Fails |
MDDYM | 83 | 43.22% | 91 | 47.40% | 81 | 40.19% | - |
PDYM | 19 | 9.90% | 14 | 7.29% | 30 | 15.63% | 4 |
MDY | 36 | 18.75% | 40 | 20.83% | 55 | 28.65% | 7 |
MFR | 23 | 11.98% | 20 | 10.42% | 26 | 13.53% | 27 |
Undecided | 31 | 16.15% | 27 | 14.06% | - | - | - |
Image & size | ObjFun | MSE | SNR | SSIM | ||||
MDDYM | MFRM | MDDYM | MFRM | MDDYM | MFRM | MDDYM | MFRM | |
Barbara |
20.66 | 19.55 | 0.80 | 0.75 | ||||
Girl |
21.73 | 21.42 | 0.77 | 0.75 | ||||
Lena |
24.29 | 22.93 | 0.90 | 0.87 | ||||
Cameraman |
21.55 | 20.05 | 0.87 | 0.83 |
Image & size | ObjFun | MSE | SNR | SSIM | ||||
MDDYM | MFRM | MDDYM | MFRM | MDDYM | MFRM | MDDYM | MFRM | |
Barbara |
20.66 | 19.55 | 0.80 | 0.75 | ||||
Girl |
21.73 | 21.42 | 0.77 | 0.75 | ||||
Lena |
24.29 | 22.93 | 0.90 | 0.87 | ||||
Cameraman |
21.55 | 20.05 | 0.87 | 0.83 |
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