glme
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)
glme
, representing
a fitted generalized 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;
else, if
"deviance"
, the deviance residuals
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 <- glme(resp ~ trt, Clinic, ~ 1 | clinic, family=binomial) ACF(fm1, maxLag=10)