02 July 2024 10:21:48.448 AM DQED_PRB1 FORTRAN90 version A set of tests for DQED, which can solve bounded and constrained linear least squares problems and systems of nonlinear equations. Example 0121C The input SIGMA vector: 1 -0.807000 2 -0.210000E-01 3 -2.37900 4 -3.64000 5 -10.5410 6 -1.96100 7 -51.5510 8 21.0530 The initial estimate for X: 1 -0.740000E-01 2 -0.733000 3 0.130000E-01 4 -0.340000E-01 5 -3.63200 6 3.63200 7 -0.289000 8 0.289000 TEST01 Use an analytic jacobian. MODE = 0 Computed minimizing X: -0.692099 -0.114901 0.710964 -0.731964 -0.815740 3.42660 1.18472 -2.33285 Residual after the fit = 0.117140E-05 DQED output flag IGO = 7 TEST01 Use an analytic jacobian. MODE = 1 Computed minimizing X: -0.692099 -0.114901 0.710964 -0.731964 -0.815740 3.42660 1.18472 -2.33285 Residual after the fit = 0.134309E-05 DQED output flag IGO = 7 TEST02 Use an approximate jacobian. MODE = 0 Computed minimizing X: -0.692099 -0.114901 0.710964 -0.731964 -0.815740 3.42660 1.18472 -2.33285 Residual after the fit = 0.754857E-06 DQED output flag IGO = 7 TEST02 Use an approximate jacobian. MODE = 1 Computed minimizing X: -0.692099 -0.114901 0.710964 -0.731964 -0.815740 3.42660 1.18472 -2.33285 Residual after the fit = 0.296953E-09 DQED output flag IGO = 2 Example 0121B The input SIGMA vector: 1 -0.809000 2 -0.210000E-01 3 -2.04000 4 -0.614000 5 -6.90300 6 -2.93400 7 -26.3280 8 18.6390 The initial estimate for X: 1 -0.560000E-01 2 -0.753000 3 0.260000E-01 4 -0.470000E-01 5 -2.99100 6 2.99100 7 -0.568000 8 0.568000 TEST01 Use an analytic jacobian. MODE = 0 Computed minimizing X: 0.903454E-02 -0.818035 -0.445074E-03 -0.205549E-01 2.77343 2.52948 -14.8010 0.522047 Residual after the fit = 0.248839E-08 DQED output flag IGO = 2 TEST01 Use an analytic jacobian. MODE = 1 Computed minimizing X: 0.903454E-02 -0.818035 -0.445074E-03 -0.205549E-01 2.77343 2.52948 -14.8010 0.522047 Residual after the fit = 0.444857E-12 DQED output flag IGO = 2 TEST02 Use an approximate jacobian. MODE = 0 Computed minimizing X: 0.903454E-02 -0.818035 -0.445074E-03 -0.205549E-01 2.77343 2.52948 -14.8010 0.522047 Residual after the fit = 0.258830E-08 DQED output flag IGO = 2 TEST02 Use an approximate jacobian. MODE = 1 Computed minimizing X: 0.903454E-02 -0.818035 -0.445074E-03 -0.205549E-01 2.77343 2.52948 -14.8010 0.522047 Residual after the fit = 0.111980E-10 DQED output flag IGO = 2 Example 0121A The input SIGMA vector: 1 -0.816000 2 -0.170000E-01 3 -1.82600 4 -0.754000 5 -4.83900 6 -3.25900 7 -14.0230 8 15.4670 The initial estimate for X: 1 -0.410000E-01 2 -0.775000 3 0.300000E-01 4 -0.470000E-01 5 -2.56500 6 2.56500 7 -0.754000 8 0.754000 TEST01 Use an analytic jacobian. MODE = 0 Computed minimizing X: 0.309987E-02 -0.819100 -0.223941E-03 -0.167761E-01 2.68151 2.25022 -20.2417 0.797098 Residual after the fit = 0.767762E-11 DQED output flag IGO = 2 TEST01 Use an analytic jacobian. MODE = 1 Computed minimizing X: 0.309987E-02 -0.819100 -0.223941E-03 -0.167761E-01 2.68151 2.25022 -20.2417 0.797098 Residual after the fit = 0.124309E-06 DQED output flag IGO = 7 TEST02 Use an approximate jacobian. MODE = 0 Computed minimizing X: 0.309987E-02 -0.819100 -0.223941E-03 -0.167761E-01 2.68151 2.25022 -20.2417 0.797098 Residual after the fit = 0.872635E-13 DQED output flag IGO = 2 TEST02 Use an approximate jacobian. MODE = 1 Computed minimizing X: 0.309987E-02 -0.819100 -0.223941E-03 -0.167761E-01 2.68151 2.25022 -20.2417 0.797098 Residual after the fit = 0.618435E-11 DQED output flag IGO = 2 Example 791226 The input SIGMA vector: 1 -0.690000 2 -0.440000E-01 3 -1.57000 4 -1.31000 5 -2.65000 6 2.00000 7 -12.6000 8 9.48000 The initial estimate for X: 1 -0.300000 2 -0.390000 3 0.300000 4 -0.344000 5 -1.20000 6 2.69000 7 1.59000 8 -1.50000 TEST01 Use an analytic jacobian. MODE = 0 Computed minimizing X: -0.311627 -0.378373 0.328244 -0.372244 -1.28223 2.49430 1.55487 -1.38464 Residual after the fit = 0.339733E-07 DQED output flag IGO = 6 TEST01 Use an analytic jacobian. MODE = 1 Computed minimizing X: -0.311627 -0.378373 0.328244 -0.372244 -1.28223 2.49430 1.55487 -1.38464 Residual after the fit = 0.339733E-07 DQED output flag IGO = 6 TEST02 Use an approximate jacobian. MODE = 0 Computed minimizing X: -0.311627 -0.378373 0.328244 -0.372244 -1.28223 2.49430 1.55487 -1.38464 Residual after the fit = 0.339778E-07 DQED output flag IGO = 6 TEST02 Use an approximate jacobian. MODE = 1 Computed minimizing X: -0.311627 -0.378373 0.328244 -0.372244 -1.28223 2.49430 1.55487 -1.38464 Residual after the fit = 0.339777E-07 DQED output flag IGO = 6 Example 791129 The input SIGMA vector: 1 0.485000 2 -0.190000E-02 3 -0.581000E-01 4 0.150000E-01 5 0.105000 6 0.406000E-01 7 0.167000 8 -0.399000 The initial estimate for X: 1 0.299000 2 0.186000 3 -0.273000E-01 4 0.254000E-01 5 -0.474000 6 0.474000 7 -0.892000E-01 8 0.892000E-01 TEST01 Use an analytic jacobian. MODE = 0 Computed minimizing X: 0.491321 -0.632135E-02 0.981564E-04 -0.199816E-02 -0.100315 0.122657 -0.207179E-01 -4.02352 Residual after the fit = 0.157406E-07 DQED output flag IGO = 7 TEST01 Use an analytic jacobian. MODE = 1 Computed minimizing X: 0.491321 -0.632135E-02 0.981564E-04 -0.199816E-02 -0.100315 0.122657 -0.207179E-01 -4.02352 Residual after the fit = 0.100733E-12 DQED output flag IGO = 2 TEST02 Use an approximate jacobian. MODE = 0 Computed minimizing X: 0.491321 -0.632135E-02 0.981564E-04 -0.199816E-02 -0.100315 0.122657 -0.207179E-01 -4.02352 Residual after the fit = 0.700672E-14 DQED output flag IGO = 2 TEST02 Use an approximate jacobian. MODE = 1 Computed minimizing X: 0.491321 -0.632135E-02 0.981562E-04 -0.199816E-02 -0.100315 0.122657 -0.207179E-01 -4.02352 Residual after the fit = 0.100201E-12 DQED output flag IGO = 2 DQED_PRB1 Normal end of execution. 02 July 2024 10:21:48.762 AM