Obtain a bootstrap replicate from incidence data — get_bootstrap

Apply a bootstrapping procedure on incidence data. Estimating Re over many bootstrapped replicates allows one to estimate the uncertainty over the estimated Re value due to observation noise. For now, only a non-parametric block bootstrapping function is implemented.

get_bootstrap_replicate(
  incidence_data,
  bootstrapping_method = "non-parametric block boostrap",
  simplify_output = TRUE,
  ...
)

Arguments

incidence_data	An object containing incidence data through time. It can either be: A list with two elements: A numeric vector named `values`: the incidence recorded on consecutive time steps. An integer named `index_offset`: the offset, counted in number of time steps, by which the first value in `values` is shifted compared to a reference time step This parameter allows one to keep track of the date of the first value in `values` without needing to carry a `date` column around. A positive offset means `values` are delayed in the future compared to the reference values. A negative offset means the opposite. A numeric vector. The vector corresponds to the `values` element descrived above, and `index_offset` is implicitely zero. This means that the first value in `incidence_data` is associated with the reference time step (no shift towards the future or past).
bootstrapping_method	string. Method to perform bootstrapping of the original incidence data. Available options are: 'non-parametric block boostrap', implemented in `.block_bootstrap`
simplify_output	boolean. Return a numeric vector instead of module output object if output offset is zero?
...	Arguments passed on to `.block_bootstrap` `round_incidence` boolean. If `TRUE`, the bootstrapped incidence is rounded to the nearest integer. `smoothing_method` string. Method used to smooth the original incidence data. Available options are: 'LOESS', implemented in `.smooth_LOESS`

Value

A list with two elements:

A numeric vector named values: the result of the computations on the input data.
An integer named index_offset: the offset, counted in number of time steps, by which the result is shifted compared to an index_offset of 0. This parameter allows one to keep track of the date of the first value in values without needing to carry a date column around. A positive offset means values are delayed in the future compared to the reference values. A negative offset means the opposite. Note that the index_offset of the output of the function call accounts for the (optional) index_offset of the input.

If index_offset is 0 and simplify_output = TRUE, the index_offset is dropped and the values element is returned as a numeric vector.

Examples

## Basic usage of get_bootstrap_replicate

bootstrap_replicate_1 <- get_bootstrap_replicate(
  HK_incidence_data$case_incidence
)


## Advanced usage of get_bootstrap_replicate
# Generate a bootstrap replicate of the incidence data, where case numbers are
# allowed to be decimal numbers, and the output is return as a list.

bootstrap_replicate_2 <- get_bootstrap_replicate(
  HK_incidence_data$case_incidence,
  simplify_output = FALSE,
  round_incidence = FALSE
)