ACF.lme {nlme} | R Documentation |

## Autocorrelation Function for lme Residuals

### Description

This method function calculates the empirical autocorrelation function
for the within-group residuals from an `lme`

fit. The
autocorrelation values are calculated using pairs of residuals within
the innermost group level. The autocorrelation function is useful for
investigating serial correlation models for equally spaced data.

### Usage

## S3 method for class 'lme':
ACF(object, maxLag, resType, ...)

### Arguments

`object` |
an object inheriting from class `lme` , representing
a fitted linear mixed-effects model. |

`maxLag` |
an optional integer giving the maximum lag for which the
autocorrelation should be calculated. Defaults to maximum lag in the
within-group residuals. |

`resType` |
an optional character string specifying the type of
residuals to be used. If `"response"` , the "raw" residuals
(observed - fitted) are used; else, if `"pearson"` , the
standardized residuals (raw residuals divided by the corresponding
standard errors) are used; else, if `"normalized"` , the
normalized residuals (standardized residuals pre-multiplied by the
inverse square-root factor of the estimated error correlation
matrix) are used. Partial matching of arguments is used, so only the
first character needs to be provided. Defaults to `"pearson"` . |

`...` |
some methods for this generic require additional
arguments – not used. |

### Value

a data frame with columns `lag`

and `ACF`

representing,
respectively, the lag between residuals within a pair and the corresponding
empirical autocorrelation. The returned value inherits from class
`ACF`

.

### 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.

Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models
in S and S-PLUS", Springer.

### See Also

`ACF.gls`

, `plot.ACF`

### Examples

fm1 <- lme(follicles ~ sin(2*pi*Time) + cos(2*pi*Time),
Ovary, random = ~ sin(2*pi*Time) | Mare)
ACF(fm1, maxLag = 11)
# Pinheiro and Bates, p240-241
fm1Over.lme <- lme(follicles ~ sin(2*pi*Time) +
cos(2*pi*Time), data=Ovary,
random=pdDiag(~sin(2*pi*Time)) )
(ACF.fm1Over <- ACF(fm1Over.lme, maxLag=10))
plot(ACF.fm1Over, alpha=0.01)

[Package

*nlme* version 3.1-80

Index]