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
build_ord_obs(),
enw_add_latest_obs_to_nowcast(),
enw_nowcast_samples(),
enw_nowcast_summary(),
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] -0.36231237 -0.35151193 0.5850323 0.6006064 -1.3159711
#> 2: expr_beta[2] -0.81956125 -0.81313828 0.5819066 0.5560748 -1.7628072
#> 3: expr_beta[3] 0.46612639 0.49545094 0.5655799 0.5622846 -0.4949055
#> 4: expr_beta[4] -0.48794876 -0.49916739 0.5589527 0.5466011 -1.3540056
#> 5: expr_beta[5] -0.22884095 -0.24754695 0.5903614 0.5921100 -1.1685938
#> 6: expr_beta[6] 1.73624712 1.70249710 0.5808644 0.5712751 0.7963793
#> 7: expr_beta[7] 0.31247778 0.30180589 0.5438900 0.5319103 -0.5481479
#> 8: expr_beta[8] 0.27411988 0.25767186 0.5339315 0.5099338 -0.6125495
#> 9: expr_beta[9] -0.37902061 -0.38080532 0.5177745 0.5149070 -1.2208034
#> 10: expr_beta[10] -0.13800267 -0.13863863 0.5126915 0.4773898 -0.9891446
#> 11: expr_beta[11] -0.56535928 -0.54510019 0.5349959 0.4969682 -1.4540302
#> 12: expr_beta[12] -1.23616337 -1.23939545 0.5669137 0.5490113 -2.2006179
#> 13: expr_beta[13] 1.52430200 1.50412600 0.6083542 0.5898186 0.5706043
#> 14: expr_beta[14] 1.80409074 1.75511405 0.5630083 0.5551297 0.9537094
#> 15: expr_beta[15] -0.21820779 -0.20997694 0.4942602 0.4706036 -0.9992519
#> 16: expr_beta[16] -0.24226832 -0.24057451 0.4896806 0.4745631 -1.0390083
#> 17: expr_beta[17] -0.18186565 -0.18607635 0.4885592 0.4840573 -0.9573425
#> 18: expr_beta[18] -0.56179968 -0.55139067 0.5233220 0.5032514 -1.4664948
#> 19: expr_beta[19] -0.32415045 -0.34557810 0.5414081 0.4867231 -1.2015871
#> 20: expr_beta[20] 1.62616667 1.60915960 0.5308494 0.5013420 0.7826004
#> 21: expr_beta[21] 0.44747037 0.44964237 0.4927074 0.4847680 -0.3446012
#> 22: expr_beta[22] -0.28153522 -0.29583439 0.4731531 0.4539509 -1.0268855
#> 23: expr_beta[23] -0.36288210 -0.35493043 0.5065852 0.4978106 -1.2188500
#> 24: expr_beta[24] -0.11913917 -0.11253562 0.5030405 0.4948383 -0.9200924
#> 25: expr_beta[25] -0.85023634 -0.84443731 0.4808408 0.4926400 -1.6473357
#> 26: expr_beta[26] -0.65606987 -0.64917948 0.5315031 0.4869885 -1.5168655
#> 27: expr_beta[27] 2.09818328 2.07172435 0.6009010 0.5828347 1.1135353
#> 28: expr_beta[28] 1.61234161 1.61686790 0.5287609 0.5388000 0.7493838
#> 29: expr_beta[29] 0.09712640 0.10143074 0.4698238 0.4568917 -0.6671413
#> 30: expr_beta[30] -0.62193854 -0.61202998 0.4911750 0.4764071 -1.4610819
#> 31: expr_beta[31] -0.25666914 -0.24656807 0.5032483 0.4953429 -1.0916028
#> 32: expr_beta[32] -0.63714072 -0.62861597 0.5150330 0.4915710 -1.4770739
#> 33: expr_beta[33] -0.14580387 -0.16495427 0.5645721 0.5251862 -1.0306670
#> 34: expr_beta[34] 1.47075466 1.44993585 0.5893215 0.5336735 0.5148384
#> 35: expr_beta[35] 0.17575746 0.16139901 0.5545039 0.5552362 -0.7371526
#> 36: expr_beta[36] 0.04687313 0.03002159 0.5723066 0.5528774 -0.8561952
#> 37: expr_beta[37] 0.08724014 0.05556753 0.5980743 0.5931941 -0.8643870
#> 38: expr_beta[38] 0.17819387 0.16938760 0.6788880 0.6819758 -0.9490598
#> 39: expr_beta[39] 0.42262333 0.42980613 0.7639196 0.7547569 -0.8700442
#> variable mean median sd mad q5
#> q20 q80 q95 rhat ess_bulk ess_tail
#> <num> <num> <num> <num> <num> <num>
#> 1: -0.87133971 0.12555731 0.56508046 0.9989587 1034.8155 784.3484
#> 2: -1.27793500 -0.35128993 0.10315747 1.0012032 1219.4900 659.5294
#> 3: -0.01216879 0.93607003 1.35838524 1.0007621 1436.5899 628.6754
#> 4: -0.95466409 -0.03895863 0.49544196 1.0008615 1124.3042 688.5391
#> 5: -0.72499127 0.26687294 0.74611517 1.0020059 1257.3737 916.6946
#> 6: 1.25857018 2.23777830 2.70428653 1.0015001 1175.0875 937.0116
#> 7: -0.11994888 0.76649043 1.20764185 0.9999581 1422.5973 797.0406
#> 8: -0.16944823 0.72601092 1.14223692 1.0006645 1271.9763 827.1159
#> 9: -0.80719373 0.04970144 0.47068590 0.9997404 1253.8721 796.6055
#> 10: -0.55146267 0.26209196 0.70929364 0.9997342 1247.4815 812.6574
#> 11: -0.97577538 -0.13774556 0.24113021 0.9996867 1167.9192 731.0374
#> 12: -1.69440914 -0.76736135 -0.34887406 1.0017817 1058.8636 813.4761
#> 13: 1.02702416 2.03352926 2.52405496 1.0059446 1064.2396 770.2097
#> 14: 1.33421322 2.28054282 2.76657796 1.0085878 938.2817 644.0399
#> 15: -0.62194760 0.16917189 0.59835233 1.0066819 1141.9916 758.6467
#> 16: -0.63600774 0.16621049 0.54314613 1.0019863 1120.5716 562.4977
#> 17: -0.61136918 0.20751536 0.63155207 1.0029007 770.5252 563.1756
#> 18: -0.98965963 -0.11010908 0.26152720 1.0013634 1130.7799 692.9768
#> 19: -0.74655571 0.09641736 0.55604595 0.9999846 1088.1731 689.8266
#> 20: 1.18499112 2.04806982 2.52287568 1.0048840 666.1959 718.7960
#> 21: 0.01769111 0.84117455 1.29764955 0.9989889 1255.2466 720.4613
#> 22: -0.67767772 0.10544919 0.51079736 1.0008952 1042.3838 667.5575
#> 23: -0.76521636 0.04122409 0.47322174 1.0011551 927.7012 677.4681
#> 24: -0.55313653 0.27715696 0.71077097 1.0055471 1234.8771 642.6127
#> 25: -1.23696004 -0.43866941 -0.09357462 1.0005179 1003.9991 732.4665
#> 26: -1.08055646 -0.24322699 0.19951345 1.0009004 1022.0853 704.1599
#> 27: 1.61533832 2.59578078 3.12353828 1.0030772 699.4889 481.3586
#> 28: 1.16813958 2.07291802 2.44034505 1.0028804 997.7398 787.7762
#> 29: -0.29967880 0.48647851 0.87632563 1.0060800 1086.4967 804.1704
#> 30: -1.02467426 -0.21999886 0.16220810 1.0057719 1074.2416 908.8440
#> 31: -0.68746043 0.16230600 0.55967256 1.0021082 1338.2938 902.4538
#> 32: -1.05282160 -0.22627583 0.17844925 1.0011134 1012.3729 646.3955
#> 33: -0.59472951 0.30289449 0.74514686 1.0036005 1104.3458 855.6841
#> 34: 1.00136246 1.92662572 2.44258336 1.0009131 1219.4466 773.5495
#> 35: -0.29302284 0.65335792 1.09055307 1.0009167 1069.8313 540.1782
#> 36: -0.42408784 0.51637944 1.02373972 1.0088049 1271.9392 723.2950
#> 37: -0.41256106 0.58398682 1.08271750 1.0031225 1570.9752 868.4931
#> 38: -0.41310494 0.76460447 1.32156526 0.9987118 1650.8947 567.5275
#> 39: -0.19550220 1.07287042 1.63541228 1.0052628 1443.3048 638.0017
#> q20 q80 q95 rhat ess_bulk ess_tail