R: Generating Covariance for Correlated Data

mkcov {gss} | R Documentation

## Generating Covariance for Correlated Data

### Description

Generate entries of covariance functions for correlated data.

### Usage

    mkcov.arma(p, q, n)
    mkcov.long(id)
    mkcov.known(w)

### Arguments

`p` | Order of AR terms.
`q` | Order of MA terms.
`n` | Dimension of covariance matrix.
`id` | Factor of subject ID.
`w` | Covariance matrix; only the upper triangular part is used.

### Details

`mkcov.arma` generates covariance functions for ARMA(p,q) model.

`mkcov.long` generates covariance functions for longitudinal data.

`mkcov.known` allows one to use a known covariance matrix in `ssanova9`.

### Value

A list of three elements.

`fun` | Covariance matrix to be evaluated through `fun(gamma,env)` or `fun(env)`.
`env` | Constants in covariance function.
`init` | Initial values for correlation parameters.

### Note

One may pass `list(fun=...,env=...,init=...)` directly to the argument `cov` in calls to `ssanova9`, or make use of the `mkcov.x` functions through `cov=list("arma",c(p,q))`, `cov=list("long",id)`, or `cov=list("known",w)`.

[Package gss version 2.2-2 Index]