nlme: ACF.gls – R documentation

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ACF.gls

Autocorrelation Function for gls Residuals

Description

This method function calculates the empirical autocorrelation function for the residuals from a gls fit. If a grouping variable is specified in form, the autocorrelation values are calculated using pairs of residuals within the same group; otherwise all possible residual pairs are used. The autocorrelation function is useful for investigating serial correlation models for equally spaced data.

Usage

## S3 method for class 'gls'
ACF(object, maxLag, resType, form, na.action, ...)

Arguments

`object`	an object inheriting from class `"gls"`, representing a generalized least squares fitted model.
`maxLag`	an optional integer giving the maximum lag for which the autocorrelation should be calculated. Defaults to maximum lag in the 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"`.
`form`	an optional one sided formula of the form `~ t`, or `~ t \| g`, specifying a time covariate `t` and, optionally, a grouping factor `g`. The time covariate must be integer valued. When a grouping factor is present in `form`, the autocorrelations are calculated using residual pairs within the same group. Defaults to `~ 1`, which corresponds to using the order of the observations in the data as a covariate, and no groups.
`na.action`	a function that indicates what should happen when the data contain `NA`s. The default action (`na.fail`) causes `ACF.gls` to print an error message and terminate if there are any incomplete observations.
`...`	some methods for this generic require additional arguments.

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)

José Pinheiro 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.

Examples

fm1 <- gls(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), Ovary)
ACF(fm1, form = ~ 1 | Mare)

# Pinheiro and Bates, p. 255-257
fm1Dial.gls <- gls(rate ~
  (pressure+I(pressure^2)+I(pressure^3)+I(pressure^4))*QB,
                   Dialyzer)

fm2Dial.gls <- update(fm1Dial.gls,
                 weights = varPower(form = ~ pressure))

ACF(fm2Dial.gls, form = ~ 1 | Subject)

nlme

Linear and Nonlinear Mixed Effects Models

v3.1-152

GPL (>= 2) | file LICENCE

Authors

José Pinheiro [aut] (S version), Douglas Bates [aut] (up to 2007), Saikat DebRoy [ctb] (up to 2002), Deepayan Sarkar [ctb] (up to 2005), EISPACK authors [ctb] (src/rs.f), Siem Heisterkamp [ctb] (Author fixed sigma), Bert Van Willigen [ctb] (Programmer fixed sigma), Johannes Ranke [ctb] (varConstProp()), R-core [aut, cre]

Initial release

2021-02-03