diff --git a/articles/web_only/basic-intro.html b/articles/web_only/basic-intro.html index 829956449..726efda0e 100644 --- a/articles/web_only/basic-intro.html +++ b/articles/web_only/basic-intro.html @@ -402,8 +402,8 @@

Model diagnostics#> #> SAMPLING FOR MODEL 'tmb_generic' NOW (CHAIN 1). #> Chain 1: -#> Chain 1: Gradient evaluation took 0.016807 seconds -#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 168.07 seconds. +#> Chain 1: Gradient evaluation took 0.024151 seconds +#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 241.51 seconds. #> Chain 1: Adjust your expectations accordingly! #> Chain 1: #> Chain 1: @@ -428,9 +428,9 @@

Model diagnostics#> Chain 1: Iteration: 100 / 101 [ 99%] (Warmup) #> Chain 1: Iteration: 101 / 101 [100%] (Sampling) #> Chain 1: -#> Chain 1: Elapsed Time: 42.615 seconds (Warm-up) -#> Chain 1: 0.313 seconds (Sampling) -#> Chain 1: 42.928 seconds (Total) +#> Chain 1: Elapsed Time: 49.432 seconds (Warm-up) +#> Chain 1: 0.38 seconds (Sampling) +#> Chain 1: 49.812 seconds (Total) #> Chain 1: r <- residuals(m3, "mle-mcmc", mcmc_samples = samps) qqnorm(r) diff --git a/articles/web_only/basic-intro_files/figure-html/plot-cv-1.png b/articles/web_only/basic-intro_files/figure-html/plot-cv-1.png index b672450b3..4954e19ee 100644 Binary files a/articles/web_only/basic-intro_files/figure-html/plot-cv-1.png and b/articles/web_only/basic-intro_files/figure-html/plot-cv-1.png differ diff --git a/articles/web_only/basic-intro_files/figure-html/residuals-1.png b/articles/web_only/basic-intro_files/figure-html/residuals-1.png index e47a1f963..fb5bb16c9 100644 Binary files a/articles/web_only/basic-intro_files/figure-html/residuals-1.png and b/articles/web_only/basic-intro_files/figure-html/residuals-1.png differ diff --git a/articles/web_only/basic-intro_files/figure-html/residuals-2.png b/articles/web_only/basic-intro_files/figure-html/residuals-2.png index 489ae8df8..92bda7a43 100644 Binary files a/articles/web_only/basic-intro_files/figure-html/residuals-2.png and b/articles/web_only/basic-intro_files/figure-html/residuals-2.png differ diff --git a/articles/web_only/basic-intro_files/figure-html/residuals-mcmc-1.png b/articles/web_only/basic-intro_files/figure-html/residuals-mcmc-1.png index d627f7114..26188be58 100644 Binary files a/articles/web_only/basic-intro_files/figure-html/residuals-mcmc-1.png and b/articles/web_only/basic-intro_files/figure-html/residuals-mcmc-1.png differ diff --git a/articles/web_only/basic-intro_files/figure-html/tv-depth-eff-1.png b/articles/web_only/basic-intro_files/figure-html/tv-depth-eff-1.png index fb2abbda3..e3720af9e 100644 Binary files a/articles/web_only/basic-intro_files/figure-html/tv-depth-eff-1.png and b/articles/web_only/basic-intro_files/figure-html/tv-depth-eff-1.png differ diff --git a/articles/web_only/bayesian.html b/articles/web_only/bayesian.html index 967e1ddeb..feeb1cc51 100644 --- a/articles/web_only/bayesian.html +++ b/articles/web_only/bayesian.html @@ -306,98 +306,98 @@

Passing the model to tmbstan#> post-warmup draws per chain=500, total post-warmup draws=1000. #> #> mean se_mean sd 2.5% 25% 50% 75% 97.5% n_eff Rhat -#> b_j[1] 0.80 0.01 0.06 0.69 0.75 0.80 0.84 0.92 40 1.08 -#> b_j[2] -0.40 0.00 0.01 -0.41 -0.40 -0.40 -0.39 -0.38 1638 1.00 -#> ln_tau_O -1.66 0.01 0.14 -1.93 -1.75 -1.65 -1.56 -1.40 375 1.00 -#> ln_phi -1.63 0.00 0.03 -1.70 -1.65 -1.63 -1.61 -1.56 2143 1.00 -#> omega_s[1] -0.08 0.01 0.09 -0.26 -0.15 -0.08 -0.01 0.09 96 1.03 -#> omega_s[2] -0.06 0.01 0.09 -0.24 -0.12 -0.06 0.01 0.13 122 1.03 -#> omega_s[3] 0.02 0.01 0.09 -0.17 -0.04 0.02 0.08 0.20 92 1.04 -#> omega_s[4] -0.20 0.01 0.10 -0.38 -0.27 -0.21 -0.14 -0.02 89 1.03 -#> omega_s[5] -0.33 0.01 0.11 -0.54 -0.40 -0.33 -0.26 -0.13 134 1.02 -#> omega_s[6] -0.07 0.01 0.11 -0.29 -0.14 -0.07 0.00 0.14 154 1.02 -#> omega_s[7] -0.02 0.01 0.08 -0.17 -0.07 -0.02 0.04 0.15 83 1.04 -#> omega_s[8] -0.22 0.01 0.09 -0.41 -0.28 -0.22 -0.16 -0.03 90 1.04 -#> omega_s[9] -0.31 0.01 0.09 -0.49 -0.37 -0.31 -0.25 -0.15 112 1.04 -#> omega_s[10] 0.29 0.01 0.09 0.10 0.23 0.29 0.35 0.48 105 1.03 -#> omega_s[11] -0.15 0.01 0.09 -0.34 -0.21 -0.15 -0.09 0.03 82 1.04 -#> omega_s[12] 0.01 0.01 0.10 -0.18 -0.06 0.01 0.07 0.22 135 1.03 -#> omega_s[13] 0.20 0.01 0.09 0.02 0.14 0.20 0.25 0.37 85 1.04 -#> omega_s[14] -0.08 0.01 0.10 -0.29 -0.15 -0.08 -0.02 0.12 152 1.03 -#> omega_s[15] 0.22 0.01 0.09 0.05 0.16 0.22 0.29 0.39 113 1.03 -#> omega_s[16] -0.01 0.01 0.09 -0.20 -0.07 0.00 0.05 0.17 100 1.04 -#> omega_s[17] -0.14 0.01 0.09 -0.32 -0.20 -0.14 -0.08 0.05 90 1.03 -#> omega_s[18] -0.28 0.01 0.10 -0.49 -0.35 -0.28 -0.21 -0.07 119 1.03 -#> omega_s[19] 0.01 0.01 0.09 -0.19 -0.05 0.01 0.07 0.18 119 1.03 -#> omega_s[20] 0.03 0.01 0.09 -0.16 -0.03 0.03 0.09 0.19 94 1.03 -#> omega_s[21] 0.09 0.01 0.10 -0.10 0.02 0.08 0.15 0.28 74 1.04 -#> omega_s[22] -0.01 0.01 0.10 -0.20 -0.08 0.00 0.07 0.18 108 1.03 -#> omega_s[23] 0.13 0.01 0.09 -0.05 0.07 0.13 0.19 0.30 96 1.03 -#> omega_s[24] 0.20 0.01 0.10 0.01 0.14 0.20 0.27 0.39 162 1.02 -#> omega_s[25] 0.08 0.01 0.09 -0.10 0.02 0.09 0.14 0.27 109 1.04 -#> omega_s[26] 0.00 0.01 0.10 -0.21 -0.07 0.00 0.06 0.19 138 1.02 -#> omega_s[27] -0.11 0.01 0.10 -0.29 -0.17 -0.10 -0.04 0.08 163 1.03 -#> omega_s[28] 0.12 0.01 0.10 -0.08 0.05 0.12 0.19 0.32 110 1.02 -#> omega_s[29] 0.30 0.01 0.09 0.12 0.25 0.30 0.37 0.47 99 1.04 -#> omega_s[30] -0.03 0.01 0.09 -0.22 -0.09 -0.03 0.03 0.14 98 1.03 -#> omega_s[31] 0.10 0.01 0.08 -0.06 0.05 0.10 0.16 0.25 70 1.05 -#> omega_s[32] 0.06 0.01 0.11 -0.18 -0.02 0.05 0.14 0.26 186 1.02 -#> omega_s[33] 0.08 0.01 0.10 -0.11 0.02 0.08 0.15 0.28 115 1.03 -#> omega_s[34] 0.05 0.01 0.09 -0.13 -0.02 0.05 0.11 0.23 128 1.03 -#> omega_s[35] 0.08 0.01 0.10 -0.10 0.02 0.08 0.14 0.27 87 1.04 -#> omega_s[36] 0.15 0.01 0.10 -0.03 0.08 0.15 0.22 0.33 113 1.04 -#> omega_s[37] 0.17 0.01 0.12 -0.06 0.09 0.17 0.24 0.40 262 1.02 -#> omega_s[38] 0.12 0.01 0.10 -0.08 0.06 0.12 0.19 0.31 113 1.03 -#> omega_s[39] -0.21 0.01 0.10 -0.40 -0.28 -0.21 -0.14 -0.03 149 1.02 -#> omega_s[40] -0.02 0.01 0.09 -0.21 -0.08 -0.02 0.05 0.16 120 1.03 -#> omega_s[41] 0.19 0.01 0.09 0.03 0.13 0.19 0.25 0.36 83 1.04 -#> omega_s[42] 0.21 0.01 0.09 0.03 0.15 0.21 0.27 0.40 103 1.03 -#> omega_s[43] 0.15 0.01 0.10 -0.05 0.08 0.15 0.22 0.35 194 1.03 -#> omega_s[44] 0.14 0.01 0.09 -0.03 0.08 0.14 0.21 0.32 101 1.03 -#> omega_s[45] 0.10 0.01 0.10 -0.10 0.03 0.10 0.16 0.29 155 1.02 -#> omega_s[46] 0.06 0.01 0.10 -0.12 0.00 0.07 0.13 0.25 142 1.02 -#> omega_s[47] 0.31 0.01 0.10 0.12 0.25 0.31 0.38 0.51 96 1.04 -#> omega_s[48] -0.24 0.01 0.09 -0.42 -0.30 -0.24 -0.18 -0.07 73 1.04 -#> omega_s[49] 0.10 0.01 0.10 -0.09 0.04 0.11 0.17 0.31 97 1.03 -#> omega_s[50] -0.08 0.01 0.09 -0.26 -0.14 -0.08 -0.02 0.09 99 1.03 -#> omega_s[51] 0.25 0.01 0.11 0.03 0.17 0.25 0.32 0.46 192 1.02 -#> omega_s[52] -0.21 0.01 0.11 -0.43 -0.28 -0.20 -0.13 0.01 89 1.03 -#> omega_s[53] 0.04 0.01 0.09 -0.14 -0.02 0.04 0.10 0.22 113 1.04 -#> omega_s[54] 0.03 0.01 0.10 -0.16 -0.04 0.03 0.10 0.23 139 1.03 -#> omega_s[55] -0.08 0.01 0.11 -0.30 -0.16 -0.08 0.00 0.14 249 1.02 -#> omega_s[56] -0.41 0.01 0.11 -0.63 -0.49 -0.41 -0.33 -0.19 131 1.02 -#> omega_s[57] 0.01 0.01 0.12 -0.21 -0.07 0.01 0.09 0.24 201 1.02 -#> omega_s[58] -0.21 0.01 0.10 -0.43 -0.27 -0.21 -0.14 -0.01 106 1.03 -#> omega_s[59] 0.05 0.01 0.24 -0.41 -0.10 0.04 0.21 0.54 892 1.00 -#> omega_s[60] -0.23 0.01 0.26 -0.77 -0.40 -0.22 -0.05 0.26 961 1.00 -#> omega_s[61] -0.25 0.01 0.23 -0.71 -0.41 -0.25 -0.09 0.18 388 1.01 -#> omega_s[62] -0.26 0.01 0.23 -0.71 -0.42 -0.26 -0.11 0.21 411 1.01 -#> omega_s[63] -0.27 0.01 0.23 -0.74 -0.43 -0.27 -0.11 0.19 443 1.01 -#> omega_s[64] 0.07 0.01 0.23 -0.35 -0.09 0.07 0.23 0.50 1007 1.00 -#> omega_s[65] 0.17 0.01 0.21 -0.23 0.02 0.17 0.29 0.60 591 1.01 -#> omega_s[66] 0.16 0.01 0.21 -0.25 0.02 0.15 0.28 0.58 573 1.01 -#> omega_s[67] -0.01 0.01 0.23 -0.49 -0.16 -0.01 0.13 0.44 1128 1.00 -#> omega_s[68] 0.00 0.01 0.25 -0.49 -0.18 0.00 0.16 0.48 1052 1.00 -#> omega_s[69] 0.01 0.01 0.21 -0.42 -0.13 0.01 0.14 0.43 681 1.00 -#> omega_s[70] 0.00 0.01 0.20 -0.41 -0.12 0.01 0.14 0.38 515 1.01 -#> omega_s[71] 0.17 0.01 0.22 -0.25 0.02 0.17 0.32 0.61 1223 1.00 -#> omega_s[72] -0.10 0.01 0.25 -0.59 -0.27 -0.11 0.06 0.37 1003 1.00 -#> omega_s[73] -0.13 0.01 0.22 -0.57 -0.27 -0.13 0.02 0.27 600 1.00 -#> omega_s[74] -0.13 0.01 0.23 -0.58 -0.27 -0.13 0.03 0.29 608 1.00 -#> omega_s[75] -0.37 0.01 0.20 -0.77 -0.50 -0.37 -0.24 0.03 535 1.00 -#> omega_s[76] 0.10 0.01 0.19 -0.28 -0.02 0.11 0.23 0.45 359 1.01 -#> omega_s[77] 0.09 0.01 0.21 -0.29 -0.06 0.08 0.24 0.50 1135 1.00 -#> omega_s[78] -0.06 0.01 0.22 -0.50 -0.20 -0.05 0.08 0.37 841 1.00 -#> omega_s[79] 0.06 0.01 0.15 -0.23 -0.05 0.05 0.16 0.33 405 1.01 -#> omega_s[80] -0.17 0.01 0.23 -0.65 -0.33 -0.17 -0.01 0.27 579 1.01 -#> omega_s[81] -0.06 0.01 0.21 -0.48 -0.19 -0.06 0.08 0.39 757 1.00 -#> omega_s[82] -0.14 0.01 0.20 -0.51 -0.28 -0.13 0.00 0.27 661 1.00 -#> omega_s[83] -0.02 0.01 0.22 -0.46 -0.16 -0.02 0.13 0.42 1066 1.00 -#> omega_s[84] 0.12 0.01 0.19 -0.25 0.00 0.12 0.25 0.52 807 1.01 -#> omega_s[85] -0.29 0.01 0.20 -0.69 -0.43 -0.28 -0.16 0.10 702 1.00 -#> lp__ 137.08 0.67 8.86 119.02 131.00 137.65 143.47 153.31 177 1.01 +#> b_j[1] 0.79 0.01 0.06 0.67 0.75 0.79 0.83 0.89 43 1.03 +#> b_j[2] -0.40 0.00 0.01 -0.42 -0.40 -0.40 -0.39 -0.38 2569 1.00 +#> ln_tau_O -1.66 0.01 0.14 -1.93 -1.76 -1.66 -1.57 -1.40 366 1.00 +#> ln_phi -1.63 0.00 0.03 -1.70 -1.65 -1.63 -1.61 -1.57 1429 1.00 +#> omega_s[1] -0.07 0.01 0.09 -0.24 -0.13 -0.07 -0.01 0.12 96 1.02 +#> omega_s[2] -0.04 0.01 0.09 -0.21 -0.10 -0.04 0.02 0.11 79 1.02 +#> omega_s[3] 0.03 0.01 0.10 -0.16 -0.04 0.03 0.09 0.23 118 1.01 +#> omega_s[4] -0.20 0.01 0.09 -0.37 -0.26 -0.19 -0.14 -0.02 116 1.00 +#> omega_s[5] -0.32 0.01 0.10 -0.53 -0.39 -0.32 -0.25 -0.13 132 1.01 +#> omega_s[6] -0.07 0.01 0.10 -0.26 -0.15 -0.07 0.00 0.13 118 1.01 +#> omega_s[7] -0.01 0.01 0.09 -0.17 -0.07 -0.01 0.05 0.15 98 1.01 +#> omega_s[8] -0.21 0.01 0.09 -0.39 -0.28 -0.21 -0.15 -0.04 103 1.01 +#> omega_s[9] -0.31 0.01 0.09 -0.48 -0.36 -0.31 -0.25 -0.14 103 1.01 +#> omega_s[10] 0.30 0.01 0.09 0.12 0.24 0.30 0.36 0.47 99 1.01 +#> omega_s[11] -0.14 0.01 0.10 -0.33 -0.20 -0.14 -0.07 0.04 100 1.01 +#> omega_s[12] 0.02 0.01 0.10 -0.19 -0.05 0.02 0.09 0.22 122 1.01 +#> omega_s[13] 0.20 0.01 0.09 0.03 0.14 0.21 0.27 0.37 93 1.01 +#> omega_s[14] -0.07 0.01 0.10 -0.26 -0.14 -0.07 -0.01 0.12 112 1.01 +#> omega_s[15] 0.23 0.01 0.09 0.07 0.17 0.23 0.30 0.41 92 1.01 +#> omega_s[16] 0.00 0.01 0.09 -0.18 -0.06 0.00 0.06 0.18 115 1.01 +#> omega_s[17] -0.13 0.01 0.10 -0.33 -0.20 -0.13 -0.07 0.06 139 1.01 +#> omega_s[18] -0.27 0.01 0.10 -0.48 -0.34 -0.27 -0.20 -0.07 154 1.01 +#> omega_s[19] 0.02 0.01 0.10 -0.18 -0.05 0.01 0.08 0.21 109 1.01 +#> omega_s[20] 0.04 0.01 0.09 -0.13 -0.02 0.04 0.10 0.22 93 1.01 +#> omega_s[21] 0.10 0.01 0.09 -0.08 0.04 0.10 0.16 0.28 110 1.02 +#> omega_s[22] 0.00 0.01 0.10 -0.18 -0.07 0.00 0.07 0.20 116 1.01 +#> omega_s[23] 0.13 0.01 0.09 -0.03 0.08 0.14 0.19 0.31 100 1.01 +#> omega_s[24] 0.21 0.01 0.10 0.01 0.14 0.20 0.28 0.41 141 1.01 +#> omega_s[25] 0.09 0.01 0.09 -0.08 0.03 0.09 0.15 0.26 94 1.01 +#> omega_s[26] 0.00 0.01 0.10 -0.21 -0.06 0.01 0.07 0.20 119 1.01 +#> omega_s[27] -0.10 0.01 0.10 -0.29 -0.16 -0.10 -0.03 0.08 103 1.01 +#> omega_s[28] 0.13 0.01 0.10 -0.07 0.06 0.13 0.19 0.33 140 1.01 +#> omega_s[29] 0.31 0.01 0.09 0.12 0.25 0.31 0.37 0.50 94 1.01 +#> omega_s[30] -0.03 0.01 0.09 -0.20 -0.08 -0.03 0.03 0.15 81 1.01 +#> omega_s[31] 0.11 0.01 0.08 -0.06 0.05 0.11 0.17 0.28 85 1.01 +#> omega_s[32] 0.06 0.01 0.12 -0.17 -0.01 0.07 0.14 0.29 186 1.01 +#> omega_s[33] 0.09 0.01 0.10 -0.09 0.03 0.09 0.16 0.28 125 1.00 +#> omega_s[34] 0.05 0.01 0.09 -0.12 -0.01 0.06 0.11 0.24 108 1.01 +#> omega_s[35] 0.09 0.01 0.09 -0.08 0.03 0.08 0.15 0.26 122 1.01 +#> omega_s[36] 0.16 0.01 0.09 -0.03 0.10 0.16 0.22 0.35 90 1.01 +#> omega_s[37] 0.17 0.01 0.11 -0.03 0.09 0.17 0.24 0.40 188 1.00 +#> omega_s[38] 0.13 0.01 0.10 -0.06 0.06 0.13 0.20 0.31 100 1.01 +#> omega_s[39] -0.20 0.01 0.09 -0.38 -0.27 -0.20 -0.14 -0.02 116 1.01 +#> omega_s[40] -0.01 0.01 0.10 -0.21 -0.08 -0.01 0.05 0.19 110 1.02 +#> omega_s[41] 0.20 0.01 0.08 0.05 0.14 0.20 0.25 0.37 84 1.02 +#> omega_s[42] 0.22 0.01 0.09 0.05 0.16 0.22 0.28 0.38 89 1.01 +#> omega_s[43] 0.16 0.01 0.10 -0.05 0.09 0.16 0.23 0.36 142 1.00 +#> omega_s[44] 0.15 0.01 0.10 -0.03 0.09 0.15 0.21 0.35 113 1.01 +#> omega_s[45] 0.11 0.01 0.11 -0.10 0.03 0.11 0.18 0.33 124 1.01 +#> omega_s[46] 0.07 0.01 0.10 -0.13 0.01 0.07 0.14 0.28 125 1.01 +#> omega_s[47] 0.32 0.01 0.09 0.15 0.26 0.32 0.38 0.51 99 1.01 +#> omega_s[48] -0.23 0.01 0.10 -0.42 -0.29 -0.23 -0.17 -0.05 107 1.01 +#> omega_s[49] 0.11 0.01 0.10 -0.09 0.04 0.11 0.18 0.32 125 1.01 +#> omega_s[50] -0.07 0.01 0.09 -0.24 -0.13 -0.07 -0.01 0.09 85 1.01 +#> omega_s[51] 0.26 0.01 0.11 0.04 0.19 0.26 0.33 0.48 142 1.01 +#> omega_s[52] -0.20 0.01 0.11 -0.42 -0.27 -0.20 -0.12 0.01 163 1.00 +#> omega_s[53] 0.05 0.01 0.10 -0.14 -0.02 0.05 0.11 0.24 101 1.01 +#> omega_s[54] 0.04 0.01 0.10 -0.14 -0.02 0.04 0.10 0.25 127 1.01 +#> omega_s[55] -0.07 0.01 0.11 -0.29 -0.15 -0.07 0.00 0.15 160 1.01 +#> omega_s[56] -0.40 0.01 0.11 -0.61 -0.47 -0.40 -0.32 -0.19 132 1.00 +#> omega_s[57] 0.02 0.01 0.11 -0.18 -0.06 0.01 0.09 0.23 131 1.00 +#> omega_s[58] -0.20 0.01 0.10 -0.38 -0.26 -0.20 -0.13 0.00 117 1.01 +#> omega_s[59] 0.06 0.01 0.24 -0.40 -0.09 0.06 0.21 0.60 780 1.00 +#> omega_s[60] -0.22 0.01 0.25 -0.72 -0.39 -0.21 -0.06 0.25 1092 1.00 +#> omega_s[61] -0.25 0.01 0.23 -0.73 -0.39 -0.24 -0.09 0.17 606 1.00 +#> omega_s[62] -0.24 0.01 0.23 -0.71 -0.39 -0.25 -0.09 0.19 506 1.00 +#> omega_s[63] -0.25 0.01 0.22 -0.69 -0.39 -0.25 -0.10 0.16 788 1.00 +#> omega_s[64] 0.09 0.01 0.23 -0.37 -0.05 0.09 0.24 0.53 1091 1.00 +#> omega_s[65] 0.17 0.01 0.22 -0.25 0.02 0.16 0.32 0.60 847 1.00 +#> omega_s[66] 0.16 0.01 0.21 -0.27 0.02 0.16 0.31 0.59 868 1.00 +#> omega_s[67] -0.01 0.01 0.24 -0.47 -0.17 -0.01 0.14 0.42 934 1.00 +#> omega_s[68] 0.00 0.01 0.25 -0.52 -0.17 0.01 0.17 0.50 625 1.00 +#> omega_s[69] 0.02 0.01 0.21 -0.40 -0.12 0.02 0.16 0.43 599 1.00 +#> omega_s[70] 0.01 0.01 0.21 -0.43 -0.12 0.02 0.15 0.40 561 1.01 +#> omega_s[71] 0.18 0.01 0.22 -0.28 0.04 0.17 0.33 0.60 1120 1.00 +#> omega_s[72] -0.11 0.01 0.24 -0.58 -0.26 -0.11 0.06 0.31 333 1.00 +#> omega_s[73] -0.14 0.01 0.21 -0.56 -0.29 -0.13 0.01 0.30 269 1.00 +#> omega_s[74] -0.13 0.01 0.21 -0.54 -0.26 -0.12 0.02 0.29 372 1.00 +#> omega_s[75] -0.36 0.01 0.21 -0.79 -0.49 -0.36 -0.22 0.05 573 1.00 +#> omega_s[76] 0.12 0.01 0.20 -0.26 -0.02 0.11 0.25 0.51 901 1.00 +#> omega_s[77] 0.09 0.01 0.20 -0.28 -0.06 0.08 0.23 0.50 798 1.00 +#> omega_s[78] -0.05 0.01 0.22 -0.47 -0.19 -0.04 0.09 0.41 456 1.00 +#> omega_s[79] 0.06 0.01 0.15 -0.26 -0.04 0.06 0.17 0.35 320 1.00 +#> omega_s[80] -0.16 0.01 0.22 -0.59 -0.31 -0.16 -0.01 0.24 676 1.00 +#> omega_s[81] -0.06 0.01 0.21 -0.44 -0.20 -0.06 0.09 0.34 472 1.00 +#> omega_s[82] -0.12 0.01 0.20 -0.53 -0.25 -0.12 0.01 0.28 567 1.00 +#> omega_s[83] 0.00 0.01 0.23 -0.45 -0.15 0.00 0.15 0.48 764 1.00 +#> omega_s[84] 0.13 0.01 0.19 -0.27 0.02 0.14 0.26 0.49 763 1.01 +#> omega_s[85] -0.28 0.01 0.21 -0.69 -0.41 -0.27 -0.13 0.12 858 1.00 +#> lp__ 136.55 0.58 8.96 118.37 130.74 136.80 142.94 153.03 242 1.00 #> -#> Samples were drawn using NUTS(diag_e) at Mon Oct 23 22:58:36 2023. +#> Samples were drawn using NUTS(diag_e) at Mon Oct 23 23:53:12 2023. #> For each parameter, n_eff is a crude measure of effective sample size, #> and Rhat is the potential scale reduction factor on split chains (at #> convergence, Rhat=1). diff --git a/articles/web_only/bayesian_files/figure-html/unnamed-chunk-12-1.png b/articles/web_only/bayesian_files/figure-html/unnamed-chunk-12-1.png index bfc9ef092..0381e6b06 100644 Binary files a/articles/web_only/bayesian_files/figure-html/unnamed-chunk-12-1.png and b/articles/web_only/bayesian_files/figure-html/unnamed-chunk-12-1.png differ diff --git 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3903245bd..281e7987f 100644 --- a/articles/web_only/cross-validation.html +++ b/articles/web_only/cross-validation.html @@ -213,9 +213,9 @@

Measuring model performance#> Set a parallel `future::plan()` to use parallel processing. m_cv$fold_loglik # fold log-likelihood -#> [1] -1687.304 -1612.128 -1629.363 -1653.811 +#> [1] -1597.910 -1765.371 -1637.951 -1636.247 m_cv$sum_loglik # total log-likelihood -#> [1] -6582.606 +#> [1] -6637.479

Single splits @@ -242,7 +242,7 @@

Single splits
 m_cv$fold_loglik[[1]]
-#> [1] -771.7377

+#> [1] -604.8126 @@ -284,9 +284,9 @@

Comparing two or more models# Compare log-likelihoods -- higher is better! m1$sum_loglik -#> [1] -6726.015 +#> [1] -6749.399 m2$sum_loglik -#> [1] -6577.048 +#> [1] -6627.266

Model ensembling diff --git a/articles/web_only/delta-models.html b/articles/web_only/delta-models.html index 479db9406..4968f4442 100644 --- a/articles/web_only/delta-models.html +++ b/articles/web_only/delta-models.html @@ -286,12 +286,14 @@

Example with built-in delta model#> #> Dispersion parameter: 1.03 #> Matérn range: 14.80 -#> Spatial SD: 0.69 +#> Spatial SD: 0.00 #> Spatiotemporal IID SD: 1.45 #> #> ML criterion at convergence: 6126.400 #> -#> See ?tidy.sdmTMB to extract these values as a data frame.

+#> See ?tidy.sdmTMB to extract these values as a data frame. +#> +#> **Possible issues detected! Check output of sanity().**

Using the tidy() function will turn the sdmTMB model output into a data frame, with the argument model=1 or model=2 to specify which model component to extract as a @@ -324,10 +326,10 @@

Example with built-in delta model#> # A tibble: 4 × 5 #> term estimate std.error conf.low conf.high #> <chr> <dbl> <dbl> <dbl> <dbl> -#> 1 range 14.8 5.02 7.62 28.8 -#> 2 phi 1.03 0.0502 0.939 1.14 -#> 3 sigma_O 0.691 0.228 0.361 1.32 -#> 4 sigma_E 1.45 0.336 0.919 2.28 +#> 1 range 14.8 5.02 7.62 28.8 +#> 2 phi 1.03 0.0502 0.939 1.14 +#> 3 sigma_O 0 0 1 1 +#> 4 sigma_E 1.45 0.336 0.919 2.28

For built-in delta models, the default function will return estimated response and parameters for each grid cell for each model separately, @@ -517,8 +519,8 @@

#> #> Dispersion parameter: 0.94 #> Matérn range: 0.01 -#> Spatial SD: 727.58 -#> Spatiotemporal IID SD: 2065.74 +#> Spatial SD: 727.59 +#> Spatiotemporal IID SD: 2065.78 #> ML criterion at convergence: 5102.136 #> #> See ?tidy.sdmTMB to extract these values as a data frame. diff --git a/articles/web_only/delta-models_files/figure-html/cv-1.png b/articles/web_only/delta-models_files/figure-html/cv-1.png index 0042c8049..ceed9bddd 100644 Binary files a/articles/web_only/delta-models_files/figure-html/cv-1.png and b/articles/web_only/delta-models_files/figure-html/cv-1.png differ diff --git a/articles/web_only/delta-models_files/figure-html/unnamed-chunk-14-1.png b/articles/web_only/delta-models_files/figure-html/unnamed-chunk-14-1.png index 9d2b53205..8353996b7 100644 Binary files a/articles/web_only/delta-models_files/figure-html/unnamed-chunk-14-1.png and b/articles/web_only/delta-models_files/figure-html/unnamed-chunk-14-1.png differ diff --git a/articles/web_only/delta-models_files/figure-html/unnamed-chunk-19-1.png b/articles/web_only/delta-models_files/figure-html/unnamed-chunk-19-1.png index 2844b6f4b..bdc073dd7 100644 Binary files a/articles/web_only/delta-models_files/figure-html/unnamed-chunk-19-1.png and b/articles/web_only/delta-models_files/figure-html/unnamed-chunk-19-1.png differ diff --git a/articles/web_only/delta-models_files/figure-html/unnamed-chunk-20-1.png b/articles/web_only/delta-models_files/figure-html/unnamed-chunk-20-1.png index b2cfb5eec..0d860b840 100644 Binary files a/articles/web_only/delta-models_files/figure-html/unnamed-chunk-20-1.png and b/articles/web_only/delta-models_files/figure-html/unnamed-chunk-20-1.png differ diff --git a/articles/web_only/ggeffects.html b/articles/web_only/ggeffects.html index 2f3dd9f22..1eabd504b 100644 --- a/articles/web_only/ggeffects.html +++ b/articles/web_only/ggeffects.html @@ -87,7 +87,7 @@

Julia Indivero, Sean Anderson, Lewis Barnett, Philina English, Eric Ward

-

2023-10-23

+

2023-10-24

Source: vignettes/web_only/ggeffects.Rmd
ggeffects.Rmd
diff --git a/articles/web_only/index-standardization.html b/articles/web_only/index-standardization.html index e0785dcc6..219c2a445 100644 --- a/articles/web_only/index-standardization.html +++ b/articles/web_only/index-standardization.html @@ -85,7 +85,7 @@

Index standardization with sdmTMB

-

2023-10-23

+

2023-10-24

Source: vignettes/web_only/index-standardization.Rmd
index-standardization.Rmd
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A conventional delta-gamma model:#> ✔ No gradients with respect to fixed effects are >= 0.001 #> ✔ No fixed-effect standard errors are NA #> ✔ No standard errors look unreasonably large -#> ✔ No sigma parameters are < 0.01 -#> ✔ No sigma parameters are > 100 +#> ✖ `sigma_O` is smaller than 0.01 +#> ℹ Consider omitting this part of the model #> ✔ Range parameters don't look unreasonably large

How can we show the effect of depth on catch weight? There is no one curve, because the two components use different links (logit + log), so @@ -264,8 +264,8 @@