Calculate 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 this data.frame or regenerate it using this function in the output of enw_preprocess_data().

## Usage

enw_delay_metadata(max_delay = 20, breaks = 4)

## Arguments

max_delay

Numeric defaults to 20. The maximum number of days to include in the delay distribution. Computation scales non-linearly with this setting so consider what maximum makes sense for your data carefully. Note that this is zero indexed and so includes the reference date and max_delay - 1 other days.

breaks

Numeric, defaults to 4. The number of breaks to use when constructing a categorised version of numeric delays.

## 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_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.

Preprocessing functions enw_add_delay(), enw_add_max_reported(), enw_add_metaobs_features(), enw_assign_group(), enw_complete_dates(), enw_construct_data(), enw_cumulative_to_incidence(), enw_delay_filter(), enw_extend_date(), enw_filter_reference_dates(), enw_filter_report_dates(), enw_incidence_to_cumulative(), enw_latest_data(), enw_metadata(), enw_missing_reference(), enw_preprocess_data(), enw_reporting_triangle_to_long(), enw_reporting_triangle()

## Examples

enw_delay_metadata(20, breaks = 4)
#>     delay delay_cat delay_week delay_tail
#>  1:     0     [0,5)          0      FALSE
#>  2:     1     [0,5)          0      FALSE
#>  3:     2     [0,5)          0      FALSE
#>  4:     3     [0,5)          0      FALSE
#>  5:     4     [0,5)          0      FALSE
#>  6:     5    [5,10)          0      FALSE
#>  7:     6    [5,10)          0      FALSE
#>  8:     7    [5,10)          1      FALSE
#>  9:     8    [5,10)          1      FALSE
#> 10:     9    [5,10)          1      FALSE
#> 11:    10   [10,15)          1      FALSE
#> 12:    11   [10,15)          1      FALSE
#> 13:    12   [10,15)          1      FALSE
#> 14:    13   [10,15)          1      FALSE
#> 15:    14   [10,15)          2      FALSE
#> 16:    15   [15,20)          2       TRUE
#> 17:    16   [15,20)          2       TRUE
#> 18:    17   [15,20)          2       TRUE
#> 19:    18   [15,20)          2       TRUE
#> 20:    19   [15,20)          2       TRUE