Bootstrap incidence time series

This function can be used to bootstrap incidence2 objects. Bootstrapping is done by sampling with replacement the original input dates.

Usage

bootstrap_incidence(x, randomise_groups = FALSE)

Arguments

x

An incidence2 object.

randomise_groups

bool.

Should groups be randomised as well in the resampling procedure; respective group sizes will be preserved, but this can be used to remove any group-specific temporal dynamics.

If FALSE (default), data are resampled within groups.

Value

An incidence2 object.

Details

As original data are not stored in incidence2 objects, the bootstrapping is achieved by multinomial sampling of date bins weighted by their relative incidence.

Author

Thibaut Jombart, Tim Taylor

Examples

if (requireNamespace("outbreaks", quietly = TRUE)) {
    data(fluH7N9_china_2013, package = "outbreaks")
    i <- incidence(
        fluH7N9_china_2013,
        date_index = "date_of_onset",
        groups = "gender"
   )
   bootstrap_incidence(i)
}
#> # incidence:  67 x 4
#> # count vars: date_of_onset
#> # groups:     gender
#>    date_index gender count_variable count
#>  * <date>     <fct>  <chr>          <int>
#>  1 2013-02-19 m      date_of_onset      0
#>  2 2013-02-27 m      date_of_onset      2
#>  3 2013-03-07 m      date_of_onset      1
#>  4 2013-03-08 m      date_of_onset      0
#>  5 2013-03-09 f      date_of_onset      0
#>  6 2013-03-13 f      date_of_onset      1
#>  7 2013-03-17 m      date_of_onset      1
#>  8 2013-03-19 f      date_of_onset      1
#>  9 2013-03-20 f      date_of_onset      2
#> 10 2013-03-20 m      date_of_onset      2
#> # ℹ 57 more rows