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
.check_primarycensored(),
.delay_draw_columns(),
.discretise_parametric_pmf(),
build_ord_obs(),
enw_add_latest_obs_to_nowcast(),
enw_nowcast_samples(),
enw_nowcast_summary(),
enw_posterior_delay(),
enw_pp_summary(),
enw_quantiles_to_long(),
enw_summarise_samples(),
subset_obs()
Examples
fit <- enw_example("nowcast")
enw_posterior(fit$fit[[1]], variables = "expr_beta")
#> variable mean median sd mad q5
#> <char> <num> <num> <num> <num> <num>
#> 1: expr_beta[1] -0.32092558 -0.302995770 0.4974060 0.5003899 -1.1751767
#> 2: expr_beta[2] -0.74265782 -0.753756680 0.4890380 0.4876114 -1.5490582
#> 3: expr_beta[3] 0.49075793 0.485267860 0.4909068 0.4815642 -0.3189382
#> 4: expr_beta[4] -0.56077281 -0.557551560 0.4827831 0.5089833 -1.3395942
#> 5: expr_beta[5] -0.38091095 -0.394056945 0.5247593 0.5420244 -1.2090794
#> 6: expr_beta[6] 1.79486180 1.789772550 0.5316671 0.5501319 0.9399786
#> 7: expr_beta[7] 0.24656509 0.238040255 0.4489022 0.4530981 -0.4740480
#> 8: expr_beta[8] 0.18508535 0.167452445 0.4515854 0.4299909 -0.5038096
#> 9: expr_beta[9] -0.31261059 -0.317163115 0.4463138 0.4614627 -1.0475074
#> 10: expr_beta[10] -0.01486819 -0.010347709 0.4220814 0.3813205 -0.7009876
#> 11: expr_beta[11] -0.61675220 -0.587198200 0.4589874 0.4705479 -1.4044386
#> 12: expr_beta[12] -1.42790779 -1.421195000 0.5044782 0.4973346 -2.2509056
#> 13: expr_beta[13] 1.62719872 1.622999750 0.5315766 0.5111194 0.7765763
#> 14: expr_beta[14] 1.79896425 1.763649550 0.4751534 0.4575447 1.0507029
#> 15: expr_beta[15] -0.25842477 -0.284254145 0.4146232 0.4247106 -0.9031172
#> 16: expr_beta[16] -0.21802551 -0.214714005 0.4273798 0.4200640 -0.9205409
#> 17: expr_beta[17] -0.04914702 -0.034840848 0.4204239 0.4048612 -0.7464496
#> 18: expr_beta[18] -0.79394694 -0.783196240 0.4063712 0.3807600 -1.4677365
#> 19: expr_beta[19] -0.51678077 -0.508444485 0.4687769 0.4601203 -1.2958871
#> 20: expr_beta[20] 1.84954623 1.852946300 0.4604705 0.4493234 1.1068935
#> 21: expr_beta[21] 0.43830304 0.429870680 0.3943223 0.4093633 -0.1897291
#> 22: expr_beta[22] -0.37514479 -0.383338120 0.3877576 0.3791090 -1.0321690
#> 23: expr_beta[23] -0.16177802 -0.161673335 0.3808587 0.3499998 -0.8074587
#> 24: expr_beta[24] -0.00725609 -0.007511365 0.3737199 0.3847101 -0.6169439
#> 25: expr_beta[25] -0.89265300 -0.872465965 0.4432475 0.4634984 -1.6111248
#> 26: expr_beta[26] -0.86827671 -0.867037245 0.4458622 0.4330594 -1.5976094
#> 27: expr_beta[27] 2.19781269 2.186659050 0.4764435 0.4831766 1.4849359
#> 28: expr_beta[28] 1.41009094 1.376479950 0.4308574 0.4191553 0.7662879
#> 29: expr_beta[29] 0.04979937 0.047622414 0.3741277 0.3795555 -0.5551349
#> 30: expr_beta[30] -0.52065898 -0.507807690 0.3997635 0.3944245 -1.1884466
#> 31: expr_beta[31] -0.13778692 -0.122675075 0.4232148 0.4005677 -0.8108834
#> 32: expr_beta[32] -0.74039628 -0.730091135 0.4162849 0.4148147 -1.4607499
#> 33: expr_beta[33] -0.38393827 -0.382522510 0.4451681 0.4618817 -1.1170769
#> 34: expr_beta[34] 1.78265989 1.769618250 0.4557591 0.4744966 1.0625023
#> 35: expr_beta[35] 0.15483523 0.148572520 0.4288613 0.4337991 -0.5316621
#> 36: expr_beta[36] 0.03436145 0.019842342 0.4642230 0.4439917 -0.6827261
#> 37: expr_beta[37] 0.01997313 0.039526770 0.4972613 0.5074665 -0.7911249
#> 38: expr_beta[38] 0.15482011 0.147784385 0.5264489 0.4984904 -0.6974510
#> 39: expr_beta[39] -0.04957734 -0.067841933 0.6669359 0.6651630 -1.0722428
#> variable mean median sd mad q5
#> <char> <num> <num> <num> <num> <num>
#> q20 q80 q95 rhat ess_bulk ess_tail
#> <num> <num> <num> <num> <num> <num>
#> 1: -0.73639250 0.090287902 0.48502811 1.0018321 878.4473 706.1199
#> 2: -1.13676816 -0.344636374 0.06348241 1.0043698 741.5364 691.1377
#> 3: 0.10044581 0.907438526 1.24770518 0.9982835 733.0923 665.0849
#> 4: -0.97341661 -0.150753668 0.22795212 1.0010690 860.5830 583.4544
#> 5: -0.81852404 0.058032422 0.46030230 1.0009878 1090.5546 797.8204
#> 6: 1.35440418 2.267011520 2.68265889 1.0015818 841.2275 735.3280
#> 7: -0.12999056 0.624345948 0.99579804 1.0009268 772.3739 798.7478
#> 8: -0.18120249 0.550547224 0.95366276 1.0045412 870.8106 750.1877
#> 9: -0.68543293 0.072643654 0.41431620 1.0028455 747.4746 684.8390
#> 10: -0.34238558 0.297214288 0.65848327 1.0009370 768.7739 689.4648
#> 11: -1.00488118 -0.217497066 0.08972751 1.0001749 982.4667 699.1044
#> 12: -1.85951502 -1.012967420 -0.60127481 1.0015900 1051.7232 689.9978
#> 13: 1.17686242 2.062967660 2.52119996 1.0046222 821.0012 796.5544
#> 14: 1.41514588 2.175821040 2.58542339 1.0045549 875.3790 794.9830
#> 15: -0.61021848 0.111923740 0.40275218 1.0037413 1189.3795 703.3240
#> 16: -0.56055053 0.128765930 0.43360164 1.0032162 975.0190 582.6757
#> 17: -0.39980843 0.305642726 0.62747661 1.0026723 1022.9964 605.9811
#> 18: -1.12668856 -0.476163362 -0.15166687 1.0084161 828.9399 724.5456
#> 19: -0.91194215 -0.132182392 0.26215119 1.0049323 849.5924 556.6769
#> 20: 1.46947150 2.216933900 2.58423808 1.0018926 821.4537 766.5134
#> 21: 0.09463508 0.781410200 1.08987256 1.0017265 653.4625 680.4379
#> 22: -0.69134303 -0.039566003 0.26008569 1.0020710 848.7761 673.0280
#> 23: -0.46726042 0.151998248 0.45985306 0.9992550 993.7858 703.3272
#> 24: -0.31956196 0.315795620 0.60201213 1.0033079 911.5141 755.1578
#> 25: -1.28310830 -0.513215950 -0.15434040 1.0021771 910.8511 824.6721
#> 26: -1.22998792 -0.512188760 -0.10110044 1.0029128 922.3267 746.6852
#> 27: 1.76485550 2.582021120 3.03506279 1.0074510 1044.4111 796.6966
#> 28: 1.04795938 1.760060540 2.20097286 1.0047873 768.8989 663.5001
#> 29: -0.26491786 0.353596022 0.66010952 1.0042307 1133.0614 725.7444
#> 30: -0.85210609 -0.197091604 0.15555015 1.0020936 914.4906 657.1161
#> 31: -0.48909516 0.190286410 0.55627997 0.9990510 1190.4347 885.7016
#> 32: -1.07899738 -0.384859026 -0.11416102 1.0000829 816.3915 574.7499
#> 33: -0.75352633 0.003764149 0.33175456 0.9988494 778.8376 750.3215
#> 34: 1.39398302 2.176802840 2.53932863 0.9994602 830.5158 741.4103
#> 35: -0.21077467 0.517067238 0.86714956 1.0007156 812.8916 630.8140
#> 36: -0.34905981 0.400178566 0.86290725 1.0043016 850.4438 573.1620
#> 37: -0.41276909 0.449751784 0.82059578 1.0024291 1186.3154 644.8023
#> 38: -0.27921994 0.572035036 1.08701899 0.9986116 1157.5990 765.7358
#> 39: -0.60852177 0.498290006 1.04315013 1.0138393 1072.8518 600.3256
#> q20 q80 q95 rhat ess_bulk ess_tail
#> <num> <num> <num> <num> <num> <num>