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
enw_add_latest_obs_to_nowcast(),
enw_nowcast_samples(),
enw_nowcast_summary(),
enw_posterior(),
enw_quantiles_to_long(),
enw_summarise_samples()
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
#> 1: 2021-07-13 2021-07-13 1 59 DE 00+ 21
#> 2: 2021-07-13 2021-07-14 1 59 DE 00+ 33
#> 3: 2021-07-13 2021-07-15 1 59 DE 00+ 36
#> 4: 2021-07-13 2021-07-16 1 59 DE 00+ 40
#> 5: 2021-07-13 2021-07-17 1 59 DE 00+ 43
#> ---
#> 626: 2021-08-20 2021-08-21 1 171 DE 00+ 159
#> 627: 2021-08-20 2021-08-22 1 171 DE 00+ 171
#> 628: 2021-08-21 2021-08-21 1 112 DE 00+ 69
#> 629: 2021-08-21 2021-08-22 1 112 DE 00+ 112
#> 630: 2021-08-22 2021-08-22 1 45 DE 00+ 45
#> cum_prop_reported delay new_confirm prop_reported mean median sd
#> 1: 0.3559322 0 21 0.35593220 23.512 22.0 9.740572
#> 2: 0.5593220 1 12 0.20338983 11.574 11.0 5.158016
#> 3: 0.6101695 2 3 0.05084746 6.492 6.0 3.540405
#> 4: 0.6779661 3 4 0.06779661 4.672 4.0 2.726509
#> 5: 0.7288136 4 3 0.05084746 2.765 3.0 1.896674
#> ---
#> 626: 0.9298246 1 61 0.35672515 47.044 43.5 19.194491
#> 627: 1.0000000 2 12 0.07017544 15.098 14.0 6.970867
#> 628: 0.6160714 0 69 0.61607143 109.043 100.0 45.345136
#> 629: 1.0000000 1 43 0.38392857 27.749 26.0 12.245814
#> 630: 1.0000000 0 45 1.00000000 52.151 49.0 23.805565
#> mad q50 rhat ess_bulk ess_tail
#> 1: 8.8956 22.0 0.9987800 1164.0127 834.6738
#> 2: 4.4478 11.0 0.9988065 1016.1220 1032.3776
#> 3: 2.9652 6.0 1.0010941 942.2827 975.7223
#> 4: 2.9652 4.0 1.0017034 817.9688 782.9234
#> 5: 1.4826 3.0 1.0007183 982.1315 914.5297
#> ---
#> 626: 17.0499 43.5 1.0056592 975.5135 913.8415
#> 627: 5.9304 14.0 0.9986250 910.5990 1033.0860
#> 628: 38.5476 100.0 1.0011913 989.3871 933.3896
#> 629: 11.8608 26.0 1.0000296 916.6473 922.1847
#> 630: 22.2390 49.0 0.9997764 1035.8098 904.4781