====== Model estimating 3 year olds and older --- monotonic survey data ===== FIXME **The plots in this section contain the following errors:** * The labels on the x-axis and the legend are three years older than they should be. (E.g. if it says 1997 it should be 1994.) * The VPA plots (solid lines with stars) are of the wrong cohorts and should be disregarded. In this section we repeat the experiments of [[admb_real:n3_cohorts_per_run|the model estimating only 3 year olds and older]], with the difference being that the survey indices which are smaller in magnitude than subsequent indices for the same cohort are deleted. This experiment is similar to [[admb_real:monotonizing_surveys|this experiment]] for [[admb_real:admb_real#model_with_two_separate_catchabilities|the model with two catchabilities]]. === Summary === :!: The estimates for this experiments are much more consistent than for the experiments with nonmonotone survey data. However, they are also usually lower, as can be seen by comparing the following table with the corresponding table [[admb_real:n3_cohorts_per_run|here]]. ^ N3birthyear ^ N31994 ^ N31995 ^ N31996 ^ N31997 ^ N31998 ^ N31999 ^ N32000 ^ ^ Single estimate |0.516109 | 0.289033 | 0.243818 | 0.443256 | | | | ^ Multiple estimates | 0.513446 | 0.298678 | | | | | | | | 0.509808 | 0.297279 | 0.250449 | | | | | | |0.504020 | 0.294245 | 0.247969 | 0.484308 | | | | | | | 0.286587 | 0.241295 | | | | | | | | 0.293470 | 0.247051 | 0.483911 | | | | | | | 0.371853 | 0.311810 | 0.615438 | 0.769912 | | | | | | | 0.268437 | 0.529506 | | | | | | | | 0.401105 | 0.812412 | 1.04852 | | | | | | | 0.281835 | 0.552476 | 0.683516 | 0.566695 | | | | | | | 0.645252 | 0.809032 | | | | | | | | 0.433931 |0.524806 |0.413599 | | | | | | | 0.406884 | 0.489518 | 0.380431 | 0.442819 | ==== First cohort born 1994 ==== ^Num. cohorts ^ Trajectories ^ Estimates ^ |1 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_94_94.png?180|}} |# Number of parameters = 4 Objective function value = -3.37978 Maximum gradient component = 1.95145e-06 # N0: 0.516109 # q: 0.475306 # logs: -0.922473038606 # M: 0.229629359685 | |2 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_94_95.png?180|}} |# Number of parameters = 5 Objective function value = -7.88727 Maximum gradient component = 3.20101e-06 # N0: 0.513446 0.298678 # q: 0.452489 # logs: -1.02581794259 # M: 0.227541762701 | |3 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_94_96.png?180|}} |# Number of parameters = 6 Objective function value = -12.6473 Maximum gradient component = 3.05992e-05 # N0: 0.509808 0.297279 0.250449 # q: 0.414260 # logs: -1.07487783663 # M: 0.224407491868 | |4 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_94_97.png?180|}} |# Number of parameters = 7 Objective function value = -20.4626 Maximum gradient component = 0.000311131 # N0: 0.504020 0.294245 0.247969 0.484308 # q: 0.417562 # logs: -1.20560858664 # M: 0.220722003756 | ==== First cohort born 1995 ==== ^Num. cohorts ^ Trajectories ^ Estimates ^ |1 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_95_95.png?180|}} |# Number of parameters = 4 Objective function value = -4.93278 Maximum gradient component = 6.89035e-06 # N0: 0.289033 # q: 0.432621 # logs: -1.20468309469 # M: 0.214608667980 | |2 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_95_96.png?180|}} |# Number of parameters = 5 Objective function value = -10.7519 Maximum gradient component = 0.000181244 # N0: 0.286587 0.241295 # q: 0.387224 # logs: -1.26799574237 # M: 0.209539869492 | |3 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_95_97.png?180|}} |# Number of parameters = 6 Objective function value = -19.7971 Maximum gradient component = 5.18349e-05 # N0: 0.293470 0.247051 0.483911 # q: 0.392993 # logs: -1.44271797754 # M: 0.218665452260 | |4 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_95_98.png?180|}} |# Number of parameters = 7 Objective function value = -22.5567 Maximum gradient component = 3.07576e-05 # N0: 0.371853 0.311810 0.615438 0.769912 # q: 0.365359 # logs: -1.30559636690 # M: 0.302854166936 | ==== First cohort born 1996 ==== ^Num. cohorts ^ Trajectories ^ Estimates ^ |1 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_96_96.png?180|}} |# Number of parameters = 4 Objective function value = -6.96424 Maximum gradient component = 2.89220e-05 # N0: 0.243818 # q: 0.341766 # logs: -1.49489079550 # M: 0.211927949874 | |2 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_96_97.png?180|}} |# Number of parameters = 5 Objective function value = -16.5870 Maximum gradient component = 7.50474e-05 # N0: 0.268437 0.529506 # q: 0.353662 # logs: -1.68478868950 # M: 0.248314995512 | |3 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_96_98.png?180|}} |# Number of parameters = 6 Objective function value = -18.1745 Maximum gradient component = 2.66569e-05 # N0: 0.401105 0.812412 1.04852 # q: 0.296806 # logs: -1.36545147740 # M: 0.384113190246 | |4 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_96_99.png?180|}} |# Number of parameters = 7 Objective function value = -21.8712 Maximum gradient component = 6.70988e-06 # N0: 0.281835 0.552476 0.683516 0.566695 # q: 0.396672 # logs: -1.28111344656 # M: 0.267739682105 | ==== First cohort born 1997 ==== ^Num. cohorts ^ Trajectories ^ Estimates ^ |1 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_97_97.png?180|}} |# Number of parameters = 4 Objective function value = -14.9417 Maximum gradient component = 0.000156633 # N0: 0.443256 # q: 0.446373 # logs: -2.63452610841 # M: 0.188376555429 | |2 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_97_98.png?180|}} |# Number of parameters = 5 Objective function value = -13.6729 Maximum gradient component = 2.55368e-05 # N0: 0.645252 0.809032 # q: 0.398800 # logs: -1.47663242459 # M: 0.322592116138 | |3 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_97_99.png?180|}} |# Number of parameters = 6 Objective function value = -17.8498 Maximum gradient component = 1.24022e-05 # N0: 0.433931 0.524806 0.413599 # q: 0.514941 # logs: -1.34998941565 # M: 0.182910597292 | |4 |{{:admb_real:cod_simple_monotonic_n3_vs_vpa_97_00.png?180|}} |# Number of parameters = 7 Objective function value = -25.7355 Maximum gradient component = 0.000543041 # N0: 0.406884 0.489518 0.380431 0.442819 # q: 0.539011 # logs: -1.41912547614 # M: 0.157823692174 |