A generic wrapper around posterior::summarise_draws() with
opinionated defaults.
Usage
enw_posterior(fit, variables = NULL, probs = c(0.05, 0.2, 0.8, 0.95), ...)Arguments
- fit
A
cmdstanrfit object.- variables
A character vector of variables to return posterior summaries for. By default summaries for all parameters are returned.
- probs
A vector of numeric probabilities to produce quantile summaries for. By default these are the 5%, 20%, 80%, and 95% quantiles which are also the minimum set required for plotting functions to work.
- ...
Additional arguments that may be passed but will not be used.
See also
Functions used for postprocessing of model fits
enw_add_latest_obs_to_nowcast(),
enw_nowcast_samples(),
enw_nowcast_summary(),
enw_pp_summary(),
enw_quantiles_to_long(),
enw_summarise_samples()
Examples
fit <- enw_example("nowcast")
enw_posterior(fit$fit[[1]], variables = "expr_beta")
#> variable mean median sd mad q5
#> 1: expr_beta[1] 0.325779775 0.310881000 0.4838097 0.4978898 -0.4580074
#> 2: expr_beta[2] -0.285751817 -0.285724500 0.4811320 0.4351924 -1.1171430
#> 3: expr_beta[3] -0.698242984 -0.689351500 0.5035263 0.4989661 -1.5294965
#> 4: expr_beta[4] 0.543736703 0.535870000 0.4792923 0.4831482 -0.2344822
#> 5: expr_beta[5] -0.573181688 -0.563478500 0.5141543 0.5216773 -1.4219590
#> 6: expr_beta[6] -0.378280841 -0.375470500 0.5119466 0.4997905 -1.2387885
#> 7: expr_beta[7] 1.696781465 1.682865000 0.4965383 0.5049661 0.9072351
#> 8: expr_beta[8] 0.274348282 0.277022000 0.4481634 0.4420225 -0.4262268
#> 9: expr_beta[9] 0.185407734 0.188547500 0.4268269 0.4158138 -0.4904147
#> 10: expr_beta[10] -0.282596234 -0.272723500 0.4504232 0.4278443 -1.0240520
#> 11: expr_beta[11] -0.047371678 -0.050473000 0.4545852 0.4564355 -0.7661744
#> 12: expr_beta[12] -0.587952299 -0.589397500 0.4588563 0.4469083 -1.3425825
#> 13: expr_beta[13] -1.409101655 -1.418430000 0.4835023 0.4724898 -2.2115425
#> 14: expr_beta[14] 1.545657074 1.527955000 0.5381898 0.5191472 0.6860950
#> 15: expr_beta[15] 1.734204724 1.748170000 0.4987449 0.4952032 0.9173902
#> 16: expr_beta[16] -0.238295058 -0.246505000 0.4485424 0.4394674 -0.9740212
#> 17: expr_beta[17] -0.165515065 -0.172435000 0.4545090 0.4660864 -0.9088496
#> 18: expr_beta[18] -0.056975132 -0.071531900 0.4073327 0.4020224 -0.7024563
#> 19: expr_beta[19] -0.655276567 -0.641959500 0.4342609 0.4283439 -1.3524920
#> 20: expr_beta[20] -0.611534005 -0.611756000 0.4451523 0.4348807 -1.3629465
#> 21: expr_beta[21] 1.765361241 1.785360000 0.4549762 0.4679827 1.0356065
#> 22: expr_beta[22] 0.426851242 0.407699000 0.4019490 0.4028921 -0.2054494
#> 23: expr_beta[23] -0.381202294 -0.375930500 0.4153174 0.4206032 -1.0500000
#> 24: expr_beta[24] -0.169577713 -0.160547000 0.4297672 0.4042761 -0.8820044
#> 25: expr_beta[25] 0.012368220 0.017780650 0.4062113 0.4014197 -0.6512639
#> 26: expr_beta[26] -0.871334871 -0.855679500 0.4373369 0.4641932 -1.5656075
#> 27: expr_beta[27] -0.866123142 -0.866338500 0.4648207 0.4607350 -1.6245060
#> 28: expr_beta[28] 2.043599679 2.055780000 0.4688895 0.4886427 1.3095775
#> 29: expr_beta[29] 1.433634728 1.401945000 0.4500883 0.4246018 0.7353343
#> 30: expr_beta[30] 0.006018938 -0.001234724 0.4319966 0.4305745 -0.6779237
#> 31: expr_beta[31] -0.455601036 -0.464617000 0.3949637 0.3897563 -1.1072715
#> 32: expr_beta[32] -0.077595866 -0.077172100 0.3950102 0.3853650 -0.7307162
#> 33: expr_beta[33] -0.667134847 -0.644114000 0.4274061 0.4381276 -1.4059055
#> 34: expr_beta[34] -0.448528434 -0.458064000 0.4650302 0.4777145 -1.1737750
#> 35: expr_beta[35] 1.688058215 1.680285000 0.4889434 0.4544317 0.9052262
#> 36: expr_beta[36] 0.273126249 0.280581000 0.4847856 0.4614257 -0.5406728
#> 37: expr_beta[37] 0.069206420 0.052811350 0.5338072 0.5185885 -0.8058002
#> 38: expr_beta[38] 0.131544949 0.136503000 0.5613003 0.5796677 -0.7853116
#> 39: expr_beta[39] 0.188225622 0.160021500 0.5643956 0.5840273 -0.6891477
#> 40: expr_beta[40] -0.279208041 -0.300830000 0.7022208 0.7073040 -1.3862745
#> variable mean median sd mad q5
#> q20 q80 q95 rhat ess_bulk ess_tail
#> 1: -0.09366416 0.76221140 1.10413450 1.0099929 1159.2004 822.9336
#> 2: -0.64690840 0.10299200 0.50504630 1.0006211 1284.8243 642.2432
#> 3: -1.13583600 -0.26579700 0.08892956 1.0001976 1285.1949 745.8015
#> 4: 0.14964800 0.93358240 1.32660300 1.0005632 1239.5051 639.7020
#> 5: -1.01438600 -0.13794600 0.23046985 0.9999926 1132.1788 779.3987
#> 6: -0.79029460 0.04244452 0.45524775 1.0038064 1060.9991 849.7843
#> 7: 1.26993200 2.12269400 2.53310800 1.0021449 999.3643 809.6835
#> 8: -0.11682600 0.65489180 1.01496700 1.0002751 1252.0844 827.4362
#> 9: -0.17673820 0.51912120 0.89033785 1.0029313 1179.2114 638.5761
#> 10: -0.66771000 0.09279750 0.42070250 0.9991341 1061.0652 882.1328
#> 11: -0.43373220 0.33166960 0.74586505 0.9998181 1164.4346 685.4559
#> 12: -0.96972360 -0.20237060 0.13261735 1.0025509 1460.8834 666.2817
#> 13: -1.80568600 -1.01381800 -0.57970910 1.0000451 1191.0922 688.8561
#> 14: 1.11683600 1.97457000 2.46249500 0.9985229 1111.5202 694.6092
#> 15: 1.30395000 2.11755000 2.61151800 1.0013222 837.5717 738.5379
#> 16: -0.60635360 0.12685800 0.51079420 0.9994091 1215.9847 796.7165
#> 17: -0.55250440 0.23580340 0.57267185 0.9987599 1319.1449 852.5114
#> 18: -0.40167640 0.29483300 0.65706110 1.0003053 1223.7983 743.5377
#> 19: -1.02691000 -0.29980140 0.06848818 1.0020510 1096.1520 795.2866
#> 20: -0.98123160 -0.23956760 0.09701997 1.0038848 974.3870 755.6643
#> 21: 1.36030400 2.13165800 2.55294500 1.0008891 897.2598 696.6751
#> 22: 0.10100138 0.74907580 1.13466150 0.9996837 923.4957 784.5132
#> 23: -0.74289220 -0.04295778 0.29470080 1.0001720 1329.9095 853.7776
#> 24: -0.51914100 0.19245760 0.52024090 1.0010176 1238.6845 898.2003
#> 25: -0.31329620 0.35625100 0.65763045 1.0001205 1124.7401 710.9356
#> 26: -1.25660800 -0.48680260 -0.21006680 1.0045389 1354.9781 938.8111
#> 27: -1.26566400 -0.48911060 -0.07998525 1.0016781 1421.4261 722.3788
#> 28: 1.62653600 2.43705400 2.79203350 1.0013443 912.9864 872.8117
#> 29: 1.07611400 1.79090000 2.19791250 1.0025878 1145.7215 663.6031
#> 30: -0.36921800 0.36803980 0.68536920 1.0026930 1228.9211 481.8507
#> 31: -0.77532080 -0.10589280 0.19159310 1.0033988 1027.3322 903.1009
#> 32: -0.39942360 0.25126780 0.55513085 1.0008729 1247.9355 681.6430
#> 33: -1.03876400 -0.31346660 -0.01804383 1.0004038 898.7760 912.4267
#> 34: -0.83913420 -0.06314966 0.32850660 1.0009000 896.6488 760.2299
#> 35: 1.29391400 2.07111600 2.48749600 1.0008372 837.8435 723.5094
#> 36: -0.11349560 0.64900200 1.11254900 1.0072449 854.4420 732.1922
#> 37: -0.36457840 0.50927900 0.97367420 1.0137967 1126.6411 637.3351
#> 38: -0.36729340 0.59653160 1.07903700 1.0149484 1103.6831 714.8289
#> 39: -0.30497160 0.65788860 1.18279200 1.0096151 1394.8641 842.4776
#> 40: -0.86686900 0.32352980 0.89831470 1.0081467 1323.5167 789.3121
#> q20 q80 q95 rhat ess_bulk ess_tail