aggregate.multi_epiparameter: Aggregate multiple <epiparameter> objects into a single...

In epiparameter: Classes and Helper Functions for Working with Epidemiological Parameters

Aggregate multiple ⁠<epiparameter>⁠ objects into a single ⁠<epiparameter>⁠ object.

Description

Combine a list of ⁠<epiparameter>⁠ objects into a single ⁠<epiparameter>⁠ with a mixture distribution [see distributional::dist_mixture()].

The aggregated ⁠<epiparameter>⁠ returned from aggregate() can then be used with the density(), cdf(), quantile() and generate() methods for the combined distributions.

Usage

## S3 method for class 'multi_epiparameter'
aggregate(x, weighting = c("equal", "sample_size", "custom"), ..., weights)

Arguments

x	A ⁠<multi_epiparameter>⁠ object.
weighting	A character string with the type of weighting to use to create the mixture distribution. Options are: "equal" for equal weighting across distributions, "sample_size" for using the sample size in each ⁠<epiparameter>⁠ object to weight the distribution (the sample sizes are normalised), or "custom" allows a vector of weights to be passed to the weights argument for a custom weighting.
...	dots Not used, will warn if extra arguments are passed to function.
weights	A numeric vector of equal length the number of ⁠<epiparameter>⁠ objects passed to x. weights is only required if weighting = "custom".

Details

The aggregate() method requires that all ⁠<epiparameter>⁠ objects are parameterised with ⁠<distribution>⁠ objects (from the distributional package). This means that unparameterised (see is_parameterised()) or discretised (see discretise()) distributions cannot be aggregated and the function will error.

Value

An ⁠<epiparameter>⁠ object

Examples

ebola_si <- epiparameter_db(epi_name = "serial interval", disease = "ebola")
aggregate(ebola_si)

epiparameter documentation built on April 3, 2025, 5:50 p.m.