A generic wrapper around enw_posterior()
with
opinionated defaults to extract the posterior prediction for the
nowcast ("pp_inf_obs"
from the stan
code). The functionality of
this function can be used directly on the output of epinowcast()
using
the supplied summary.epinowcast()
method.
Usage
enw_nowcast_summary(fit, obs, probs = c(0.05, 0.2, 0.35, 0.5, 0.65, 0.8, 0.95))
Arguments
- fit
A
cmdstanr
fit object.- obs
An observation
data.frame
containingreference_date
columns of the same length as the number of rows in the posterior and the most up to date observation for each date. This is used to align the posterior with the observations. The easiest source of this data is the output of latest output ofenw_preprocess_data()
orenw_latest_data()
.- 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.
Value
A data.frame
summarising the model posterior nowcast prediction.
This uses observed data where available and the posterior prediction
where not.
See also
Functions used for postprocessing of model fits
enw_add_latest_obs_to_nowcast()
,
enw_nowcast_samples()
,
enw_posterior()
,
enw_pp_summary()
,
enw_quantiles_to_long()
,
enw_summarise_samples()
Examples
fit <- enw_example("nowcast")
enw_nowcast_summary(fit$fit[[1]], fit$latest[[1]])
#> reference_date report_date .group max_confirm location age_group confirm
#> 1: 2021-08-03 2021-08-22 1 149 DE 00+ 149
#> 2: 2021-08-04 2021-08-22 1 166 DE 00+ 166
#> 3: 2021-08-05 2021-08-22 1 133 DE 00+ 133
#> 4: 2021-08-06 2021-08-22 1 137 DE 00+ 137
#> 5: 2021-08-07 2021-08-22 1 139 DE 00+ 139
#> 6: 2021-08-08 2021-08-22 1 97 DE 00+ 97
#> 7: 2021-08-09 2021-08-22 1 58 DE 00+ 58
#> 8: 2021-08-10 2021-08-22 1 175 DE 00+ 175
#> 9: 2021-08-11 2021-08-22 1 233 DE 00+ 233
#> 10: 2021-08-12 2021-08-22 1 237 DE 00+ 237
#> 11: 2021-08-13 2021-08-22 1 204 DE 00+ 204
#> 12: 2021-08-14 2021-08-22 1 189 DE 00+ 189
#> 13: 2021-08-15 2021-08-22 1 125 DE 00+ 125
#> 14: 2021-08-16 2021-08-22 1 98 DE 00+ 98
#> 15: 2021-08-17 2021-08-22 1 242 DE 00+ 242
#> 16: 2021-08-18 2021-08-22 1 223 DE 00+ 223
#> 17: 2021-08-19 2021-08-22 1 202 DE 00+ 202
#> 18: 2021-08-20 2021-08-22 1 171 DE 00+ 171
#> 19: 2021-08-21 2021-08-22 1 112 DE 00+ 112
#> 20: 2021-08-22 2021-08-22 1 45 DE 00+ 45
#> cum_prop_reported delay prop_reported mean median sd mad q5
#> 1: 1 19 0.000000000 149.000 149.0 0.000000 0.0000 149
#> 2: 1 18 0.000000000 167.453 167.0 1.291301 1.4826 166
#> 3: 1 17 0.000000000 135.677 135.0 1.853674 1.4826 133
#> 4: 1 16 0.000000000 140.896 141.0 2.169768 2.9652 138
#> 5: 1 15 0.007194245 145.222 145.0 2.760133 2.9652 141
#> 6: 1 14 0.000000000 103.248 103.0 2.893591 2.9652 99
#> 7: 1 13 0.000000000 62.742 62.0 2.412313 2.9652 59
#> 8: 1 12 0.000000000 185.065 185.0 3.687054 4.4478 180
#> 9: 1 11 0.000000000 255.574 255.0 6.079925 5.9304 246
#> 10: 1 10 0.004219409 266.480 266.0 7.480345 7.4130 255
#> 11: 1 9 0.000000000 235.082 235.0 7.671123 7.4130 224
#> 12: 1 8 0.015873016 229.150 229.0 9.532280 10.3782 215
#> 13: 1 7 0.040000000 163.327 163.0 8.941478 8.8956 149
#> 14: 1 6 0.010204082 130.404 130.0 8.343284 8.8956 118
#> 15: 1 5 0.012396694 299.890 299.0 12.795923 13.3434 280
#> 16: 1 4 0.017937220 303.138 301.0 17.375755 17.0499 278
#> 17: 1 3 0.019801980 311.131 309.0 24.503638 23.7216 275
#> 18: 1 2 0.070175439 318.522 315.0 34.923992 34.0998 270
#> 19: 1 1 0.383928571 334.231 327.5 53.967621 51.1497 258
#> 20: 1 0 1.000000000 322.430 306.0 93.868922 80.8017 198
#> q20 q35 q50 q65 q80 q95 rhat ess_bulk ess_tail
#> 1: 149.0 149.00 149.0 149.00 149.0 149.00 NA NA NA
#> 2: 166.0 167.00 167.0 168.00 168.0 170.00 1.0002481 858.3035 887.5883
#> 3: 134.0 135.00 135.0 136.00 137.0 139.00 0.9986872 784.2638 908.5946
#> 4: 139.0 140.00 141.0 142.00 143.0 145.00 0.9999757 986.1909 904.5245
#> 5: 143.0 144.00 145.0 146.00 147.0 150.00 1.0007676 865.5054 947.2221
#> 6: 101.0 102.00 103.0 104.00 106.0 109.00 0.9991973 893.3750 835.9871
#> 7: 61.0 62.00 62.0 63.00 65.0 67.00 1.0036034 926.5402 861.1900
#> 8: 182.0 183.00 185.0 186.00 188.0 191.00 0.9989872 1097.4089 937.1445
#> 9: 251.0 253.00 255.0 258.00 261.0 266.00 0.9991648 1111.3917 1021.2936
#> 10: 260.0 263.00 266.0 269.00 272.0 279.05 1.0073591 1059.0036 983.0723
#> 11: 228.0 232.00 235.0 237.35 241.0 248.00 1.0012317 975.8115 927.8796
#> 12: 221.0 225.00 229.0 232.00 237.0 246.00 0.9999872 1084.7105 951.3275
#> 13: 155.0 159.00 163.0 166.00 171.0 178.00 0.9994459 1041.2300 974.4463
#> 14: 123.0 127.00 130.0 133.00 137.0 145.00 1.0012796 935.7652 1050.2310
#> 15: 289.0 294.00 299.0 304.00 310.2 322.00 1.0017171 1130.4067 958.2443
#> 16: 288.8 295.00 301.0 308.00 317.0 334.05 1.0055266 848.0051 763.8073
#> 17: 291.0 300.65 309.0 317.35 329.0 356.00 1.0105072 1083.0271 1028.2641
#> 18: 288.8 303.00 315.0 330.00 343.2 383.00 1.0047446 1063.6034 939.8372
#> 19: 288.8 308.00 327.5 347.00 375.0 436.00 1.0005068 1007.8998 874.2774
#> 20: 247.8 276.00 306.0 340.35 390.2 493.05 1.0003640 1366.8407 840.3280