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.
ACF(object, maxLag, resType)
lme
, representing
a fitted linear mixed-effects model.
"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"
.
lag
and
ACF
representing,
respectively, the lag between residuals within a pair and the corresponding
empirical autocorrelation. The returned value inherits from class
ACF
.
Box, G.E.P., Jenkins, G.M., and Reinsel G.C. (1994) "Time Series Analysis: Forecasting and Control", 3rd Edition, Holden-Day.
fm1 <- lme(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), Ovary, random = ~ sin(2*pi*Time) | Mare) ACF(fm1, maxLag = 11)