# hhh4_internals: Internal Functions Dealing with 'hhh4' Models In surveillance: Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena

## Description

The functions documented here are considered internal, i.e., not intended to be called by the user. They are used by add-on packages dealing with `hhh4` models.

## Usage

 ```1 2 3 4``` ```meanHHH(theta, model, subset = model\$subset, total.only = FALSE) sizeHHH(theta, model, subset = model\$subset) decompose.hhh4(x, coefs = x\$coefficients, ...) ```

## Arguments

 `theta,coefs` numeric vector of model parameters. `model` the model terms as returned by the `terms`-method for `"hhh4"` objects. `subset` vector of time points for which to compute the component means. Defaults to the fitted time range. For `sizeHHH`, `subset=NULL` means to return the vector of dispersion parameters. `total.only` logical. Should only the total mean (epidemic + endemic) be returned in a `length(subset)` x nUnit matrix? Otherwise, a list of such matrices is returned, giving the values of the various model components separately (as well as the total). `x` a fitted `hhh4` model. `...` unused.

## Details

`meanHHH` computes the components of the mean returned in `length(subset)` x nUnit matrices. `sizeHHH` computes the model dispersion in `dnbinom` (`mu`, `size`) parametrization (it returns `NULL` in the Poisson case). `decompose.hhh4` decomposes the fitted mean (extracted via `meanHHH`) in an array with dimensions (t, i, j), where the first j index is `"endemic"`.

## Author(s)

Michaela Paul and Sebastian Meyer

surveillance documentation built on March 31, 2021, 9:08 a.m.