Calculate reporting delay metadata for a given maximum delay
Source:R/preprocess.R
enw_metadata_delay.RdCalculate delay metadata based on the supplied maximum delay and independent
of other metadata or date indexing. These data are meant to be used in
conjunction with metadata on the date of reference. Users can build
additional features with this data.frame or regenerate it using this
function in the output of enw_preprocess_data().
Arguments
- max_delay
The maximum number of days to model in the delay distribution. Must be an integer greater than or equal to 1. Observations with delays larger then the maximum delay will be dropped. If the specified maximum delay is too short, nowcasts can be biased as important parts of the true delay distribution are cut off. At the same time, computational cost scales non-linearly with this setting, so you want the maximum delay to be as long as necessary, but not much longer. Consider what delays are realistic for your application, and when in doubt, check if increasing the maximum delay noticeably changes the delay distribution or nowcasts as estimated by epinowcast. If it does, your maximum delay may still be too short. Note that delays are zero indexed and so include the reference date and
max_delay - 1other days (i.e. amax_delayof 1 corresponds to no delay). You can usecheck_max_delay()to check the coverage of a delay distribution for different maximum delays.- breaks
Numeric, defaults to 4. The number of breaks to use when constructing a categorised version of numeric delays.
- timestep
The timestep to used. This can be a string ("day", "week", "month") or a numeric whole number representing the number of days.
Value
A data.frame of delay metadata. This includes:
delay: The numeric delay from reference date to report.delay_cat: The categorised delay. This may be useful for model building.delay_week: The numeric week since the delay was reported. This again may be useful for model building.delay_head: A logical variable defining if the delay is in the lower 25% of the potential delays. This may be particularly useful when building models that assume a parametric distribution in order to increase the weight of the head of the reporting distribution in a pragmatic way.delay_tail: A logical variable defining if the delay is in the upper 75% of the potential delays. This may be particularly useful when building models that assume a parametric distribution in order to increase the weight of the tail of the reporting distribution in a pragmatic way.
See also
Preprocessing functions
enw_add_delay(),
enw_add_max_reported(),
enw_add_metaobs_features(),
enw_assign_group(),
enw_complete_dates(),
enw_construct_data(),
enw_extend_date(),
enw_filter_delay(),
enw_filter_reference_dates(),
enw_filter_report_dates(),
enw_flag_observed_observations(),
enw_impute_na_observations(),
enw_latest_data(),
enw_metadata(),
enw_missing_reference(),
enw_preprocess_data(),
enw_reporting_triangle(),
enw_reporting_triangle_to_long()
Examples
enw_metadata_delay(max_delay = 20, breaks = 4)
#> delay delay_cat delay_week delay_head delay_tail
#> <int> <fctr> <int> <lgcl> <lgcl>
#> 1: 0 [0,5) 0 TRUE FALSE
#> 2: 1 [0,5) 0 TRUE FALSE
#> 3: 2 [0,5) 0 TRUE FALSE
#> 4: 3 [0,5) 0 TRUE FALSE
#> 5: 4 [0,5) 0 TRUE FALSE
#> 6: 5 [5,10) 0 FALSE FALSE
#> 7: 6 [5,10) 0 FALSE FALSE
#> 8: 7 [5,10) 1 FALSE FALSE
#> 9: 8 [5,10) 1 FALSE FALSE
#> 10: 9 [5,10) 1 FALSE FALSE
#> 11: 10 [10,15) 1 FALSE FALSE
#> 12: 11 [10,15) 1 FALSE FALSE
#> 13: 12 [10,15) 1 FALSE FALSE
#> 14: 13 [10,15) 1 FALSE FALSE
#> 15: 14 [10,15) 2 FALSE FALSE
#> 16: 15 [15,20) 2 FALSE TRUE
#> 17: 16 [15,20) 2 FALSE TRUE
#> 18: 17 [15,20) 2 FALSE TRUE
#> 19: 18 [15,20) 2 FALSE TRUE
#> 20: 19 [15,20) 2 FALSE TRUE
#> delay delay_cat delay_week delay_head delay_tail