corARMA {nlme} | R Documentation |

## ARMA(p,q) Correlation Structure

### Description

This function is a constructor for the `corARMA`

class,
representing an autocorrelation-moving average correlation structure
of order (p, q). Objects created using this constructor must later
be initialized using the appropriate `Initialize`

method.

### Usage

corARMA(value, form, p, q, fixed)

### Arguments

`value` |
a vector with the values of the autoregressive and moving
average parameters, which must have length `p + q` and all
elements between -1 and 1. Defaults to a vector of zeros,
corresponding to uncorrelated observations. |

`form` |
a one sided formula of the form `~ t` , or ```
~ t |
g
``` , specifying a time covariate `t` and, optionally, a
grouping factor `g` . A covariate for this correlation structure
must be integer valued. When a grouping factor is present in
`form` , the correlation structure is assumed to apply only
to observations within the same grouping level; observations with
different grouping levels are assumed to be uncorrelated. Defaults to
`~ 1` , which corresponds to using the order of the observations
in the data as a covariate, and no groups. |

`p, q` |
non-negative integers specifying respectively the
autoregressive order and the moving average order of the `ARMA`
structure. Both default to 0. |

`fixed` |
an optional logical value indicating whether the
coefficients should be allowed to vary in the optimization, or kept
fixed at their initial value. Defaults to `FALSE` , in which case
the coefficients are allowed to vary. |

### Value

an object of class `corARMA`

, representing an
autocorrelation-moving average correlation structure.

### Author(s)

Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates bates@stat.wisc.edu

### References

Box, G.E.P., Jenkins, G.M., and Reinsel G.C. (1994) "Time Series
Analysis: Forecasting and Control", 3rd Edition, Holden-Day.

### See Also

`Initialize.corStruct`

### Examples

## ARMA(1,2) structure, with observation order as a covariate and
## Mare as grouping factor
cs1 <- corARMA(c(0.2, 0.3, -0.1), form = ~ 1 | Mare, p = 1, q = 2)

[Package

*nlme* version 3.1-57

Index]