covariates | R Documentation |

Incorporating time-varying covariates using lookup tables.

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

`...` |
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 |

`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. |

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()`

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