# covariate_table: Covariates In pomp: Statistical Inference for Partially Observed Markov Processes

 covariates R Documentation

## Covariates

### Description

Incorporating time-varying covariates using lookup tables.

### Usage

```## S4 method for signature 'numeric'
covariate_table(..., order = c("linear", "constant"), times)

## S4 method for signature 'character'
covariate_table(..., order = c("linear", "constant"), times)
```

### Arguments

 `...` numeric vectors or data frames containing time-varying covariates. It must be possible to bind these into a data frame. `order` the order of interpolation to be used. Options are “linear” (the default) and “constant”. Setting `order="linear"` treats the covariates as piecewise linear functions of time; `order="constant"` treats them as right-continuous piecewise constant functions. `times` the times corresponding to the covariates. This may be given as a vector of (non-decreasing, finite) numerical values. Alternatively, one can specify by name which of the given variables is the time variable.

### Details

If the ‘pomp’ object contains covariates (specified via the `covar` argument), then interpolated values of the covariates will be available to each of the model components whenever it is called. In particular, variables with names as they appear in the `covar` covariate table will be available to any C snippet. When a basic component is defined using an R function, that function will be called with an extra argument, `covars`, which will be a named numeric vector containing the interpolated values from the covariate table.

An exception to this rule is the prior (`rprior` and `dprior`): covariate-dependent priors are not allowed. Nor are parameter transformations permitted to depend upon covariates.

More on implementing POMP models: `Csnippet`, `accumulator variables`, `basic components`, `betabinomial`, `distributions`, `dmeasure specification`, `dprocess specification`, `emeasure specification`, `parameter transformations`, `pomp-package`, `pomp`, `prior specification`, `rinit specification`, `rmeasure specification`, `rprocess specification`, `skeleton specification`, `transformations`, `userdata`, `vmeasure specification`
More on interpolation: `bsplines`, `lookup()`