Extract posterior draws for the named parameters into a wide data frame,
one row per draw and one column per parameter, alongside the .chain,
.iteration and .draw bookkeeping columns.
Parameters are named unquoted, and a name matches every indexed element it
prefixes, so beta_num reaches beta_num[1], beta_num[2] and so on.
Usage
draws_wide(object, ..., regex = FALSE, ndraws = NULL)
# S3 method for class 'ratiod_fit'
draws_wide(object, ..., regex = FALSE, ndraws = NULL)Examples
# \donttest{
# Generate synthetic data
set.seed(222)
n <- 48
site <- rep(letters[1:12], each = 4)
u <- rnorm(12, sd = 0.5)[match(site, letters[1:12])]
depth <- rnorm(n)
df <- data.frame(
count = rpois(n, exp(3 + 0.3 * depth + u)),
effort = rgamma(n, shape = 10, rate = exp(-u)),
depth = depth,
site = site
)
# Fit model
fit <- tratio(
count | effort ~ depth + (1 | site),
data = df,
family = ratiod_poisson_gamma(),
mode = "hmc",
control = list(iter = 400, chains = 1, seed = 1)
)
# Extract fixed effects
draws_wide(fit, beta_num, beta_denom)
#> .chain .iteration .draw beta_num[1] beta_num[2] beta_denom[1] beta_denom[2]
#> 1 1 1 1 3.101985 0.3068892 2.459224 -0.0120378751
#> 2 1 2 2 3.105241 0.3079707 2.453971 -0.0082497659
#> 3 1 3 3 3.105156 0.2494162 2.439193 -0.0499355673
#> 4 1 4 4 3.167302 0.2809653 2.494543 0.0105590162
#> 5 1 5 5 3.191217 0.2755134 2.477328 -0.0050317610
#> 6 1 6 6 3.191217 0.2755134 2.477328 -0.0050317610
#> 7 1 7 7 3.191217 0.2755134 2.477328 -0.0050317610
#> 8 1 8 8 3.187972 0.2887279 2.565870 -0.0036675950
#> 9 1 9 9 3.210911 0.2881958 2.545209 0.0042936087
#> 10 1 10 10 3.301703 0.2723997 2.645708 -0.0573598334
#> 11 1 11 11 3.310025 0.2825577 2.614350 -0.0405140140
#> 12 1 12 12 3.299086 0.2766005 2.630947 -0.0338474217
#> 13 1 13 13 3.220290 0.3051411 2.557528 -0.0220401483
#> 14 1 14 14 3.266614 0.2993117 2.515841 0.0252417963
#> 15 1 15 15 3.292277 0.2945589 2.569610 0.0315784486
#> 16 1 16 16 3.306576 0.3048949 2.606331 -0.0280556206
#> 17 1 17 17 3.280041 0.2995562 2.649594 -0.0428207667
#> 18 1 18 18 3.275025 0.2925270 2.619035 -0.0576760223
#> 19 1 19 19 3.267042 0.2724673 2.566917 0.0173055727
#> 20 1 20 20 3.278715 0.2774054 2.554827 0.0525509901
#> 21 1 21 21 3.278715 0.2774054 2.554827 0.0525509901
#> 22 1 22 22 3.296677 0.2705124 2.626019 0.0156032463
#> 23 1 23 23 3.310552 0.3073983 2.672674 -0.0680562681
#> 24 1 24 24 3.339746 0.3185517 2.575219 -0.1744165619
#> 25 1 25 25 3.339746 0.3185517 2.575219 -0.1744165619
#> 26 1 26 26 3.283649 0.3351999 2.685325 -0.1533601156
#> 27 1 27 27 3.281714 0.3242921 2.639316 0.0486194484
#> 28 1 28 28 3.336337 0.2432410 2.536762 -0.0483901625
#> 29 1 29 29 3.185169 0.2401978 2.538735 0.0315094790
#> 30 1 30 30 3.187784 0.2362610 2.503011 0.0717015087
#> 31 1 31 31 3.217263 0.2149376 2.478036 0.0804206272
#> 32 1 32 32 3.215137 0.2220358 2.494762 0.0625142575
#> 33 1 33 33 3.162152 0.2130510 2.505149 0.0668281193
#> 34 1 34 34 3.192231 0.2488850 2.566961 0.0805866962
#> 35 1 35 35 3.170471 0.2964014 2.512192 0.1125233792
#> 36 1 36 36 3.127532 0.2974061 2.522757 0.0003978798
#> 37 1 37 37 3.182705 0.2727274 2.390193 0.0112024856
#> 38 1 38 38 2.960457 0.2977132 2.292518 -0.0244619453
#> 39 1 39 39 3.080451 0.2952046 2.398013 0.0136942713
#> 40 1 40 40 3.065825 0.2847779 2.362375 0.0177713704
#> 41 1 41 41 3.073080 0.2851172 2.370697 0.0328846456
#> 42 1 42 42 3.047797 0.2852089 2.395536 0.0450196185
#> 43 1 43 43 3.128909 0.2633020 2.432834 0.0419355892
#> 44 1 44 44 3.128909 0.2633020 2.432834 0.0419355892
#> 45 1 45 45 3.110272 0.2605307 2.422890 0.0557521417
#> 46 1 46 46 3.131414 0.2585419 2.356748 0.0564728750
#> 47 1 47 47 3.110215 0.2803613 2.338990 -0.0575696838
#> 48 1 48 48 3.128160 0.3053558 2.308202 0.0164107703
#> 49 1 49 49 3.018209 0.2808484 2.406668 0.0187443899
#> 50 1 50 50 3.096426 0.2822738 2.355495 -0.0494811988
#> 51 1 51 51 3.070148 0.2803799 2.391760 -0.0601141274
#> 52 1 52 52 3.103458 0.2950128 2.423718 0.0584683115
#> 53 1 53 53 3.049844 0.3101326 2.405815 0.0378512315
#> 54 1 54 54 3.217321 0.3229377 2.498233 -0.0527769902
#> 55 1 55 55 3.146562 0.3100842 2.512866 -0.0754335053
#> 56 1 56 56 3.146562 0.3100842 2.512866 -0.0754335053
#> 57 1 57 57 3.102236 0.2356807 2.472331 -0.0601313848
#> 58 1 58 58 3.054289 0.3051440 2.340131 -0.0263070565
#> 59 1 59 59 3.054289 0.3051440 2.340131 -0.0263070565
#> 60 1 60 60 2.911579 0.3126521 2.280352 -0.0181967147
#> 61 1 61 61 2.914558 0.3089141 2.304724 -0.0577620138
#> 62 1 62 62 3.114119 0.2516652 2.434809 -0.0236545255
#> 63 1 63 63 3.089362 0.2237694 2.403868 0.0178805628
#> 64 1 64 64 3.100027 0.2129389 2.388324 0.0213037499
#> 65 1 65 65 3.176627 0.3091204 2.539045 -0.1341674603
#> 66 1 66 66 3.113400 0.2358979 2.401223 0.1113007042
#> 67 1 67 67 3.107954 0.2492133 2.420895 -0.0116489039
#> 68 1 68 68 3.103513 0.2458340 2.432625 -0.0254594164
#> 69 1 69 69 3.034687 0.3318500 2.360034 -0.0201227743
#> 70 1 70 70 3.071397 0.3210315 2.381668 -0.0178818607
#> 71 1 71 71 2.975731 0.2764193 2.327219 0.0809653494
#> 72 1 72 72 2.992361 0.2774307 2.346785 0.0847252214
#> 73 1 73 73 3.088239 0.2696393 2.366877 0.0738767711
#> 74 1 74 74 3.038682 0.2704890 2.383376 0.0722304165
#> 75 1 75 75 2.922660 0.2570262 2.314755 -0.0879631764
#> 76 1 76 76 3.005813 0.2680420 2.256647 -0.0923093328
#> 77 1 77 77 3.006420 0.2385199 2.300691 -0.0199676768
#> 78 1 78 78 2.911457 0.2727967 2.213877 0.0383731649
#> 79 1 79 79 2.935812 0.2666657 2.117977 0.0238740990
#> 80 1 80 80 2.916888 0.2596522 2.128389 0.0271136924
#> 81 1 81 81 2.755533 0.2413568 2.140941 -0.1208902189
#> 82 1 82 82 2.786074 0.2005353 1.996314 -0.0418619480
#> 83 1 83 83 2.775990 0.1979044 1.964602 -0.0449246925
#> 84 1 84 84 2.823443 0.2224342 2.193234 -0.0492130601
#> 85 1 85 85 2.768115 0.2500390 2.040574 -0.0938200880
#> 86 1 86 86 2.731982 0.2547702 2.158301 -0.1173923484
#> 87 1 87 87 2.749266 0.2541401 2.139210 -0.1184296361
#> 88 1 88 88 2.614640 0.2490343 1.981126 -0.0062791390
#> 89 1 89 89 2.618113 0.2517948 1.984008 -0.0039955365
#> 90 1 90 90 2.636177 0.2389255 1.928102 -0.0395742361
#> 91 1 91 91 2.633810 0.2418624 1.917174 -0.0465479775
#> 92 1 92 92 3.169445 0.3206796 2.502669 -0.0520581287
#> 93 1 93 93 3.141311 0.2821829 2.464518 0.0006364339
#> 94 1 94 94 3.003144 0.2263277 2.183078 0.0115865798
#> 95 1 95 95 3.046194 0.2300931 2.224406 0.0196329433
#> 96 1 96 96 2.971028 0.3413540 2.300212 0.0506884180
#> 97 1 97 97 2.764416 0.2397957 2.033862 -0.0208321835
#> 98 1 98 98 2.769581 0.2525088 2.008314 -0.0163629247
#> 99 1 99 99 2.739054 0.2522300 2.010885 -0.0193561351
#> 100 1 100 100 3.113374 0.2766511 2.475398 -0.0417700661
#> 101 1 101 101 3.194819 0.1886530 2.471484 -0.0234614860
#> 102 1 102 102 2.976962 0.3042277 2.293486 -0.0400590211
#> 103 1 103 103 2.973769 0.3062311 2.288910 -0.0562245674
#> 104 1 104 104 3.012125 0.2832661 2.304313 -0.0357239376
#> 105 1 105 105 2.955296 0.2592508 2.269114 -0.0540400508
#> 106 1 106 106 3.045409 0.2991752 2.307710 -0.0227375123
#> 107 1 107 107 3.015676 0.2855060 2.285555 -0.0526352184
#> 108 1 108 108 2.999168 0.2994244 2.273307 -0.0370535223
#> 109 1 109 109 3.006928 0.2897504 2.385795 -0.0309175072
#> 110 1 110 110 2.991332 0.3571342 2.410392 -0.0257535424
#> 111 1 111 111 3.014932 0.3553714 2.407958 -0.0199290810
#> 112 1 112 112 3.026073 0.3363493 2.325200 -0.0556101659
#> 113 1 113 113 3.037506 0.3324425 2.331497 -0.0504389200
#> 114 1 114 114 3.006268 0.2872720 2.382760 -0.0038445112
#> 115 1 115 115 3.047982 0.2872414 2.392288 -0.0047324912
#> 116 1 116 116 3.114297 0.3222603 2.315490 0.0380961856
#> 117 1 117 117 3.085950 0.3159689 2.359727 0.0506234250
#> 118 1 118 118 3.085950 0.3159689 2.359727 0.0506234250
#> 119 1 119 119 3.056514 0.3347669 2.308591 0.0174841633
#> 120 1 120 120 3.116908 0.3107285 2.437937 -0.0506170639
#> 121 1 121 121 3.096864 0.3069135 2.359241 -0.0372787641
#> 122 1 122 122 3.160128 0.2338568 2.393204 -0.0425598193
#> 123 1 123 123 3.114799 0.2340010 2.412542 -0.0590172491
#> 124 1 124 124 3.134529 0.2378052 2.471506 -0.1157695123
#> 125 1 125 125 3.301237 0.3525362 2.605775 0.0768604087
#> 126 1 126 126 3.279390 0.3354462 2.612413 0.0944078108
#> 127 1 127 127 3.237686 0.3270955 2.640771 0.0937473595
#> 128 1 128 128 3.322031 0.2902594 2.651992 0.0304932665
#> 129 1 129 129 3.190450 0.2841822 2.538719 0.0922262997
#> 130 1 130 130 3.253995 0.2859548 2.514724 -0.0969825942
#> 131 1 131 131 3.218132 0.2773608 2.501613 -0.0396267641
#> 132 1 132 132 3.182173 0.2834687 2.471285 0.0307735318
#> 133 1 133 133 3.180179 0.2849539 2.499380 0.0325049024
#> 134 1 134 134 3.304369 0.3123284 2.635999 0.0139566149
#> 135 1 135 135 3.330930 0.3164014 2.620609 0.0009294787
#> 136 1 136 136 3.299403 0.3273481 2.679477 0.0592129393
#> 137 1 137 137 3.119325 0.2210586 2.492484 -0.0298107918
#> 138 1 138 138 3.163200 0.2634172 2.567630 -0.0745148653
#> 139 1 139 139 3.184098 0.2751110 2.495199 -0.0968514003
#> 140 1 140 140 3.179495 0.2480586 2.485916 -0.0292107937
#> 141 1 141 141 3.174582 0.2455486 2.515194 0.0208277241
#> 142 1 142 142 3.169091 0.2499690 2.538117 -0.0576159536
#> 143 1 143 143 3.093192 0.3072483 2.356461 -0.0218878262
#> 144 1 144 144 3.093192 0.3072483 2.356461 -0.0218878262
#> 145 1 145 145 3.156310 0.2420737 2.530730 -0.0125907454
#> 146 1 146 146 3.135998 0.2715006 2.590674 0.0263685131
#> 147 1 147 147 3.198336 0.2960400 2.364449 -0.0215250411
#> 148 1 148 148 3.212133 0.2732911 2.664560 -0.0045598001
#> 149 1 149 149 3.220001 0.2368241 2.568622 0.0605525253
#> 150 1 150 150 3.225636 0.2448742 2.523791 0.0848804383
#> 151 1 151 151 3.168293 0.2405480 2.534829 -0.0301921451
#> 152 1 152 152 3.149638 0.2870003 2.483155 -0.0700565386
#> 153 1 153 153 3.148922 0.2924723 2.478224 -0.0617232402
#> 154 1 154 154 3.177675 0.2954758 2.473161 -0.0511031729
#> 155 1 155 155 3.117158 0.2406642 2.458628 -0.0181593768
#> 156 1 156 156 3.117158 0.2406642 2.458628 -0.0181593768
#> 157 1 157 157 3.016561 0.3253588 2.394376 -0.1200218576
#> 158 1 158 158 3.018564 0.2991474 2.350989 -0.0560412779
#> 159 1 159 159 3.068382 0.3162327 2.383238 -0.0760121700
#> 160 1 160 160 3.053520 0.3175182 2.414638 -0.0754610433
#> 161 1 161 161 2.998841 0.3033425 2.366800 -0.0822438531
#> 162 1 162 162 2.989350 0.3078855 2.320715 -0.0690568483
#> 163 1 163 163 2.986486 0.2516286 2.275931 -0.0884616965
#> 164 1 164 164 2.986486 0.2516286 2.275931 -0.0884616965
#> 165 1 165 165 3.008339 0.2602259 2.249624 -0.0839532237
#> 166 1 166 166 3.016313 0.2445913 2.241720 0.0003853206
#> 167 1 167 167 2.949294 0.2600004 2.277051 0.0008410025
#> 168 1 168 168 2.966717 0.2969027 2.238100 -0.0127988547
#> 169 1 169 169 2.836073 0.2720076 2.247654 0.0445463281
#> 170 1 170 170 3.074001 0.3229635 2.412755 -0.1243401685
#> 171 1 171 171 2.946276 0.3159987 2.331851 -0.0274038550
#> 172 1 172 172 2.946276 0.3159987 2.331851 -0.0274038550
#> 173 1 173 173 3.062858 0.2955384 2.348110 0.0491112504
#> 174 1 174 174 2.960062 0.2823592 2.340683 0.0677965603
#> 175 1 175 175 2.967520 0.2814751 2.391157 0.0515204065
#> 176 1 176 176 3.086628 0.2806010 2.311536 0.0077255837
#> 177 1 177 177 3.113674 0.2889407 2.406510 -0.0132769046
#> 178 1 178 178 2.949133 0.3099792 2.317243 0.0432748866
#> 179 1 179 179 2.913433 0.2058020 2.247976 -0.0503876436
#> 180 1 180 180 2.921175 0.1962022 2.215520 -0.0984038197
#> 181 1 181 181 2.966194 0.2431586 2.236049 -0.0143283147
#> 182 1 182 182 3.006890 0.2245199 2.307466 -0.0272551659
#> 183 1 183 183 3.145061 0.3219809 2.441798 -0.0029435074
#> 184 1 184 184 3.310204 0.2562204 2.598787 -0.0072522626
#> 185 1 185 185 3.206556 0.2656761 2.585558 -0.0227813160
#> 186 1 186 186 3.360258 0.2398982 2.686583 -0.0695567952
#> 187 1 187 187 3.404625 0.2289572 2.710186 -0.0424531971
#> 188 1 188 188 3.376222 0.2014800 2.642033 0.0130020163
#> 189 1 189 189 3.421926 0.2148287 2.692609 -0.0321273701
#> 190 1 190 190 3.430823 0.2092495 2.629947 -0.0352987579
#> 191 1 191 191 3.398340 0.2235817 2.691630 -0.0018887669
#> 192 1 192 192 3.379762 0.2183785 2.743037 -0.0045009381
#> 193 1 193 193 3.379762 0.2183785 2.743037 -0.0045009381
#> 194 1 194 194 3.367943 0.3466827 2.729227 -0.0565521546
#> 195 1 195 195 3.367943 0.3466827 2.729227 -0.0565521546
#> 196 1 196 196 3.483255 0.3048267 2.788573 -0.0720608813
#> 197 1 197 197 3.444774 0.2777781 2.668544 -0.0421694274
#> 198 1 198 198 3.421999 0.2998557 2.844019 -0.0020021156
#> 199 1 199 199 2.944616 0.2977051 2.275037 -0.0455066708
#> 200 1 200 200 2.944616 0.2977051 2.275037 -0.0455066708
# Subsample draws
draws_wide(fit, sigma_re, ndraws = 100)
#> .chain .iteration .draw sigma_re
#> 134 1 134 1 0.7813137
#> 167 1 167 2 0.4374382
#> 191 1 191 3 0.6746877
#> 22 1 22 4 0.5216152
#> 40 1 40 5 0.5185618
#> 183 1 183 6 1.1357260
#> 156 1 156 7 0.5319757
#> 90 1 90 8 0.9482283
#> 62 1 62 9 0.6332759
#> 41 1 41 10 0.5474304
#> 18 1 18 11 0.5130855
#> 74 1 74 12 0.3586224
#> 17 1 17 13 0.4806656
#> 123 1 123 14 0.4391662
#> 197 1 197 15 0.6535350
#> 59 1 59 16 0.5927881
#> 83 1 83 17 0.7094891
#> 145 1 145 18 0.5018967
#> 131 1 131 19 0.4481307
#> 135 1 135 20 0.8298446
#> 58 1 58 21 0.5927881
#> 117 1 117 22 0.4740734
#> 64 1 64 23 0.6476529
#> 75 1 75 24 0.7296752
#> 14 1 14 25 0.4724080
#> 72 1 72 26 0.4098247
#> 84 1 84 27 0.6456905
#> 199 1 199 28 0.4633979
#> 93 1 93 29 0.5193471
#> 25 1 25 30 0.4915418
#> 104 1 104 31 0.4664518
#> 163 1 163 32 0.5317328
#> 103 1 103 33 0.4519865
#> 119 1 119 34 0.5600445
#> 44 1 44 35 0.4560379
#> 171 1 171 36 0.5070362
#> 24 1 24 37 0.4915418
#> 111 1 111 38 0.3233151
#> 172 1 172 39 0.5070362
#> 96 1 96 40 0.6262807
#> 56 1 56 41 0.5434028
#> 188 1 188 42 0.8873059
#> 154 1 154 43 0.5423282
#> 140 1 140 44 0.4380254
#> 23 1 23 45 0.6274048
#> 185 1 185 46 0.9331735
#> 33 1 33 47 0.7441958
#> 166 1 166 48 0.4079692
#> 67 1 67 49 0.4403988
#> 39 1 39 50 0.5907458
#> 15 1 15 51 0.4387835
#> 53 1 53 52 0.4607365
#> 35 1 35 53 0.5647673
#> 182 1 182 54 0.7724533
#> 158 1 158 55 0.5446587
#> 81 1 81 56 0.5980823
#> 164 1 164 57 0.5317328
#> 87 1 87 58 0.6947940
#> 126 1 126 59 0.3992705
#> 177 1 177 60 0.4468147
#> 122 1 122 61 0.3781115
#> 190 1 190 62 0.7132576
#> 116 1 116 63 0.4734875
#> 175 1 175 64 0.4811869
#> 120 1 120 65 0.3969654
#> 31 1 31 66 0.6360443
#> 38 1 38 67 0.6639300
#> 97 1 97 68 0.9373942
#> 100 1 100 69 0.4272832
#> 88 1 88 70 0.9410728
#> 106 1 106 71 0.4127289
#> 179 1 179 72 0.6168502
#> 65 1 65 73 0.9884453
#> 129 1 129 74 0.4309796
#> 73 1 73 75 0.3681839
#> 153 1 153 76 0.4936113
#> 187 1 187 77 0.9077191
#> 127 1 127 78 0.3972801
#> 107 1 107 79 0.3449943
#> 114 1 114 80 0.4048662
#> 50 1 50 81 0.5432276
#> 147 1 147 82 0.5096714
#> 150 1 150 83 0.5969032
#> 159 1 159 84 0.4805500
#> 63 1 63 85 0.6657896
#> 125 1 125 86 0.4274163
#> 146 1 146 87 0.5278470
#> 99 1 99 88 0.9724078
#> 71 1 71 89 0.4036248
#> 95 1 95 90 0.5540441
#> 42 1 42 91 0.5331618
#> 98 1 98 92 0.9975874
#> 6 1 6 93 0.6189147
#> 7 1 7 94 0.6189147
#> 36 1 36 95 0.7663849
#> 115 1 115 96 0.3953993
#> 2 1 2 97 0.8382185
#> 80 1 80 98 0.7511201
#> 110 1 110 99 0.3351862
#> 160 1 160 100 0.4820052
# }