This function summarises posterior predictives
for observed data (by report and reference date). The functionality of
this function can be used directly on the output of epinowcast() using
the supplied summary.epinowcast() method.
Usage
enw_pp_summary(fit, diff_obs, probs = c(0.05, 0.2, 0.35, 0.5, 0.65, 0.8, 0.95))Arguments
- fit
A
cmdstanrfit object.- diff_obs
A
data.frameof observed data with at least a date variablereference_date, and a grouping variable.group.- 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.
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_posterior(),
enw_quantiles_to_long(),
enw_summarise_samples(),
subset_obs()
Examples
fit <- enw_example("nowcast")
enw_pp_summary(fit$fit[[1]], fit$new_confirm[[1]], probs = c(0.5))
#> reference_date report_date .group max_confirm location age_group confirm
#> <IDat> <IDat> <num> <int> <fctr> <fctr> <int>
#> 1: 2021-07-14 2021-07-14 1 72 DE 00+ 22
#> 2: 2021-07-14 2021-07-15 1 72 DE 00+ 34
#> 3: 2021-07-14 2021-07-16 1 72 DE 00+ 38
#> 4: 2021-07-14 2021-07-17 1 72 DE 00+ 43
#> 5: 2021-07-14 2021-07-18 1 72 DE 00+ 43
#> ---
#> 606: 2021-08-20 2021-08-21 1 171 DE 00+ 159
#> 607: 2021-08-20 2021-08-22 1 171 DE 00+ 171
#> 608: 2021-08-21 2021-08-21 1 112 DE 00+ 69
#> 609: 2021-08-21 2021-08-22 1 112 DE 00+ 112
#> 610: 2021-08-22 2021-08-22 1 45 DE 00+ 45
#> cum_prop_reported delay new_confirm prop_reported mean median sd
#> <num> <num> <int> <num> <num> <num> <num>
#> 1: 0.3055556 0 22 0.30555556 22.049 20 10.447476
#> 2: 0.4722222 1 12 0.16666667 22.031 21 10.062370
#> 3: 0.5277778 2 4 0.05555556 7.992 8 4.118361
#> 4: 0.5972222 3 5 0.06944444 4.261 4 2.692978
#> 5: 0.5972222 4 0 0.00000000 1.326 1 1.258295
#> ---
#> 606: 0.9298246 1 61 0.35672515 81.048 77 33.870413
#> 607: 1.0000000 2 12 0.07017544 12.586 11 6.299229
#> 608: 0.6160714 0 69 0.61607143 73.471 69 32.792995
#> 609: 1.0000000 1 43 0.38392857 47.332 44 20.074730
#> 610: 1.0000000 0 45 1.00000000 40.534 37 20.435911
#> mad q50 rhat ess_bulk ess_tail
#> <num> <num> <num> <num> <num>
#> 1: 8.8956 20 1.0007087 981.0605 957.4820
#> 2: 10.3782 21 1.0006400 1010.0549 860.7285
#> 3: 4.4478 8 1.0018374 1046.7610 956.3804
#> 4: 2.9652 4 1.0008338 959.7921 978.0414
#> 5: 1.4826 1 1.0003294 999.1432 873.2038
#> ---
#> 606: 31.1346 77 0.9999674 1016.8230 1000.9385
#> 607: 5.9304 11 1.0006309 965.7202 850.5506
#> 608: 29.6520 69 0.9983329 1072.1422 973.6582
#> 609: 19.2738 44 0.9993679 1127.5257 906.6164
#> 610: 17.7912 37 1.0003136 1372.2704 1042.6714