summary method for class "epinowcast".
Arguments
- object
A
data.tableoutput fromepinowcast().- type
Character string indicating the summary to return; enforced by
base::match.arg(). Supported options are:"nowcast" which summarises nowcast posterior with
enw_nowcast_summary(),"nowcast_samples" which samples latest with
enw_nowcast_samples(),"fit" which returns the summarised
cmdstanrfit withenw_posterior(),"posterior_prediction" which returns summarised posterior predictions for the observations after fitting using
enw_pp_summary().
- max_delay
Maximum delay to which nowcasts should be summarised. Must be equal (default) or larger than the modelled maximum delay. If it is larger, then nowcasts for unmodelled dates are added by assuming that case counts beyond the modelled maximum delay are fully observed.
- ...
Additional arguments passed to summary specified by
type.
See also
summary epinowcast
Other epinowcast:
epinowcast(),
plot.epinowcast()
Examples
nowcast <- enw_example("nowcast")
# Summarise nowcast posterior
summary(nowcast, type = "nowcast")
#> reference_date report_date .group max_confirm location age_group confirm
#> <IDat> <IDat> <num> <int> <fctr> <fctr> <int>
#> 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
#> reference_date report_date .group max_confirm location age_group confirm
#> cum_prop_reported delay prop_reported mean median sd mad
#> <num> <num> <num> <num> <num> <num> <num>
#> 1: 1 19 0.000000000 149.000 149 0.000000 0.0000
#> 2: 1 18 0.000000000 167.426 167 1.318432 1.4826
#> 3: 1 17 0.000000000 135.789 136 1.854162 1.4826
#> 4: 1 16 0.000000000 141.288 141 2.378805 1.4826
#> 5: 1 15 0.007194245 146.019 146 3.079630 2.9652
#> 6: 1 14 0.000000000 103.853 104 2.969884 2.9652
#> 7: 1 13 0.000000000 62.766 63 2.432110 2.9652
#> 8: 1 12 0.000000000 185.035 185 3.847932 4.4478
#> 9: 1 11 0.000000000 256.031 256 6.498790 5.9304
#> 10: 1 10 0.004219409 267.692 267 7.713536 7.4130
#> 11: 1 9 0.000000000 236.057 235 8.508004 7.4130
#> 12: 1 8 0.015873016 231.407 231 10.083304 10.3782
#> 13: 1 7 0.040000000 164.876 164 9.848127 10.3782
#> 14: 1 6 0.010204082 128.858 128 8.134495 7.4130
#> 15: 1 5 0.012396694 293.309 292 11.938427 11.8608
#> 16: 1 4 0.017937220 293.042 292 15.799489 14.8260
#> 17: 1 3 0.019801980 291.478 290 21.108128 19.2738
#> 18: 1 2 0.070175439 293.178 291 29.440398 28.1694
#> 19: 1 1 0.383928571 308.518 302 51.151522 46.7019
#> 20: 1 0 1.000000000 375.644 363 103.424281 91.1799
#> cum_prop_reported delay prop_reported mean median sd mad
#> q5 q20 q35 q50 q65 q80 q95 rhat ess_bulk ess_tail
#> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num>
#> 1: 149.00 149 149.00 149 149.00 149 149.00 NA NA NA
#> 2: 166.00 166 167.00 167 168.00 168 170.00 0.9997778 1003.5643 828.2026
#> 3: 133.00 134 135.00 136 136.00 137 139.00 1.0005878 991.0805 916.0962
#> 4: 138.00 139 140.00 141 142.00 143 146.00 1.0056729 1041.2029 872.9772
#> 5: 141.00 143 145.00 146 147.00 148 152.00 1.0001025 991.1639 885.1056
#> 6: 100.00 101 102.65 104 105.00 106 109.00 0.9991163 982.3833 917.3468
#> 7: 59.00 61 62.00 63 63.00 65 67.00 1.0009067 911.2098 793.6687
#> 8: 179.00 182 183.00 185 186.00 188 192.00 1.0002531 1004.7790 972.0392
#> 9: 246.00 251 253.00 256 258.00 261 268.00 0.9997137 1025.3311 936.5679
#> 10: 256.00 261 265.00 267 270.00 274 282.00 1.0004951 1040.1417 1008.8448
#> 11: 223.00 229 233.00 235 239.00 243 251.00 0.9985724 1201.4893 863.9704
#> 12: 216.00 222 227.00 231 234.00 240 250.00 1.0035756 751.4194 655.0188
#> 13: 150.00 157 160.00 164 168.00 173 181.00 1.0025186 927.9122 920.9413
#> 14: 117.00 122 125.00 128 131.00 135 143.00 1.0010009 1080.4014 964.2083
#> 15: 276.00 283 288.00 292 297.00 303 315.00 1.0002316 1159.2978 984.6276
#> 16: 268.00 280 286.00 292 299.00 306 320.00 1.0047058 1087.6045 957.9921
#> 17: 260.00 274 282.00 290 298.35 308 330.00 1.0002334 1129.6391 914.6275
#> 18: 250.00 269 280.00 291 301.00 316 344.00 0.9993186 1126.3831 903.3288
#> 19: 239.00 267 286.00 302 322.00 343 399.10 0.9992178 1328.2832 998.7573
#> 20: 233.95 292 327.00 363 397.00 447 565.05 0.9991666 1554.0485 999.3402
#> q5 q20 q35 q50 q65 q80 q95 rhat ess_bulk ess_tail
# Nowcast posterior samples
summary(nowcast, type = "nowcast_samples")
#> reference_date report_date .group max_confirm location age_group confirm
#> <IDat> <IDat> <num> <int> <fctr> <fctr> <int>
#> 1: 2021-08-03 2021-08-22 1 149 DE 00+ 149
#> 2: 2021-08-03 2021-08-22 1 149 DE 00+ 149
#> 3: 2021-08-03 2021-08-22 1 149 DE 00+ 149
#> 4: 2021-08-03 2021-08-22 1 149 DE 00+ 149
#> 5: 2021-08-03 2021-08-22 1 149 DE 00+ 149
#> ---
#> 19996: 2021-08-22 2021-08-22 1 45 DE 00+ 45
#> 19997: 2021-08-22 2021-08-22 1 45 DE 00+ 45
#> 19998: 2021-08-22 2021-08-22 1 45 DE 00+ 45
#> 19999: 2021-08-22 2021-08-22 1 45 DE 00+ 45
#> 20000: 2021-08-22 2021-08-22 1 45 DE 00+ 45
#> cum_prop_reported delay prop_reported .chain .iteration .draw sample
#> <num> <num> <num> <int> <int> <int> <num>
#> 1: 1 19 0 1 1 1 149
#> 2: 1 19 0 1 2 2 149
#> 3: 1 19 0 1 3 3 149
#> 4: 1 19 0 1 4 4 149
#> 5: 1 19 0 1 5 5 149
#> ---
#> 19996: 1 0 1 2 496 996 338
#> 19997: 1 0 1 2 497 997 598
#> 19998: 1 0 1 2 498 998 219
#> 19999: 1 0 1 2 499 999 508
#> 20000: 1 0 1 2 500 1000 297
# Nowcast model fit
summary(nowcast, type = "fit")
#> variable mean median sd mad
#> <char> <num> <num> <num> <num>
#> 1: lp__ -1373.3815400 -1372.7100000 7.4386468 7.1831970
#> 2: expr_lelatent_int[1,1] 4.1775366 4.1753300 0.1807851 0.1778527
#> 3: expr_beta[1] 0.3568452 0.3851365 0.6071031 0.5922742
#> 4: expr_beta[2] -0.3387549 -0.3541355 0.5316359 0.5444528
#> 5: expr_beta[3] -0.8258812 -0.8167105 0.5264853 0.5388206
#> ---
#> 852: pp_inf_obs[16,1] 293.0420000 292.0000000 15.7994892 14.8260000
#> 853: pp_inf_obs[17,1] 291.4780000 290.0000000 21.1081280 19.2738000
#> 854: pp_inf_obs[18,1] 293.1780000 291.0000000 29.4403983 28.1694000
#> 855: pp_inf_obs[19,1] 308.5180000 302.0000000 51.1515215 46.7019000
#> 856: pp_inf_obs[20,1] 375.6440000 363.0000000 103.4242807 91.1799000
#> q5 q20 q80 q95 rhat
#> <num> <num> <num> <num> <num>
#> 1: -1386.3515000 -1379.3860000 -1367.2600000 -1.362146e+03 1.0165644
#> 2: 3.8798325 4.0294840 4.3297920 4.480233e+00 1.0003207
#> 3: -0.6494806 -0.1630136 0.8722602 1.317674e+00 1.0001047
#> 4: -1.2489460 -0.7875022 0.1375294 5.137213e-01 1.0029342
#> 5: -1.6927830 -1.2671460 -0.3640068 -1.222673e-02 1.0007299
#> ---
#> 852: 268.0000000 280.0000000 306.0000000 3.200000e+02 1.0047058
#> 853: 260.0000000 274.0000000 308.0000000 3.300000e+02 1.0002334
#> 854: 250.0000000 269.0000000 316.0000000 3.440000e+02 0.9993186
#> 855: 239.0000000 267.0000000 343.0000000 3.991000e+02 0.9992178
#> 856: 233.9500000 292.0000000 447.0000000 5.650500e+02 0.9991666
#> ess_bulk ess_tail
#> <num> <num>
#> 1: 202.8285 433.4364
#> 2: 990.9203 725.2305
#> 3: 867.1216 773.7010
#> 4: 1370.1095 692.4391
#> 5: 1019.0570 680.3411
#> ---
#> 852: 1087.6045 957.9921
#> 853: 1129.6391 914.6275
#> 854: 1126.3831 903.3288
#> 855: 1328.2832 998.7573
#> 856: 1554.0485 999.3402
# Posterior predictions
summary(nowcast, type = "posterior_prediction")
#> reference_date report_date .group max_confirm location age_group confirm
#> <IDat> <IDat> <num> <int> <fctr> <fctr> <int>
#> 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
#> <num> <num> <int> <num> <num> <num> <num>
#> 1: 0.3559322 0 21 0.35593220 19.639 19 8.642649
#> 2: 0.5593220 1 12 0.20338983 20.812 19 9.566932
#> 3: 0.6101695 2 3 0.05084746 6.137 6 3.627311
#> 4: 0.6779661 3 4 0.06779661 4.147 4 2.595019
#> 5: 0.7288136 4 3 0.05084746 2.396 2 1.842438
#> ---
#> 626: 0.9298246 1 61 0.35672515 79.760 76 31.667100
#> 627: 1.0000000 2 12 0.07017544 12.362 11 6.193328
#> 628: 0.6160714 0 69 0.61607143 74.098 70 30.701090
#> 629: 1.0000000 1 43 0.38392857 47.543 43 22.022605
#> 630: 1.0000000 0 45 1.00000000 40.036 37 18.937617
#> mad q5 q20 q35 q50 q65 q80 q95 rhat ess_bulk
#> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num>
#> 1: 8.8956 7 12 15 19 22 27 35.00 0.9998578 950.1480
#> 2: 8.8956 8 13 16 19 23 28 38.00 0.9996637 806.5805
#> 3: 2.9652 1 3 4 6 7 9 13.00 1.0032698 967.3662
#> 4: 2.9652 1 2 3 4 5 6 9.00 0.9991688 1110.2815
#> 5: 1.4826 0 1 1 2 3 4 6.00 0.9996678 896.9374
#> ---
#> 626: 31.1346 36 53 65 76 87 104 137.05 1.0003079 1054.6289
#> 627: 5.9304 4 7 9 11 14 17 24.00 1.0025396 998.3479
#> 628: 29.6520 31 48 60 70 81 96 128.05 0.9988369 1194.4760
#> 629: 19.2738 20 30 37 43 52 62 91.00 1.0010545 1154.8141
#> 630: 17.7912 16 23 30 37 44 55 75.00 0.9993409 1159.6413
#> ess_tail
#> <num>
#> 1: 983.7776
#> 2: 667.5845
#> 3: 1001.0476
#> 4: 975.4648
#> 5: 922.8697
#> ---
#> 626: 881.3948
#> 627: 1035.5098
#> 628: 1028.2922
#> 629: 814.1646
#> 630: 855.4762