Fit a Subsampled Bootstrap to Integer Values and Summarise Distribution Parameters

Fits an integer adjusted distribution to a subsampled bootstrap of data and then integrates the posterior samples into a single set of summary statistics. Can be used to generate a robust reporting delay that accounts for the fact the underlying delay likely varies over time or that the size of the available reporting delay sample may not be representative of the current case load.

bootstrapped_dist_fit(
  values,
  dist = "lognormal",
  samples = 2000,
  bootstraps = 10,
  bootstrap_samples = 250,
  max_value,
  verbose = FALSE
)

Arguments

values: Integer vector of values.
dist: Character string, which distribution to fit. Defaults to lognormal ("lognormal") but gamma ("gamma") is also supported.
samples: Numeric, number of samples to take overall from the bootstrapped posteriors.
bootstraps: Numeric, defaults to 1. The number of bootstrap samples (with replacement) of the delay distribution to take.
bootstrap_samples: Numeric, defaults to 100. The number of samples to take in each bootstrap. When the sample size of the supplied delay distribution is less than 100 this is used instead.
max_value: Numeric, defaults to the maximum value in the observed data. Maximum delay to allow (added to output but does impact fitting).
verbose: Logical, defaults to FALSE. Should progress messages be printed

Value

A list summarising the bootstrapped distribution

Examples

# \donttest{
# lognormal
delays <- rlnorm(500, log(5), 1)
out <- bootstrapped_dist_fit(delays,
  samples = 1000, bootstraps = 10,
  dist = "lognormal"
)
out
#> $mean
#> [1] 1.473848
#> 
#> $mean_sd
#> [1] 0.09470087
#> 
#> $sd
#> [1] 1.143309
#> 
#> $sd_sd
#> [1] 0.070004
#> 
#> $max
#> [1] 98
#> 
# }