lme
fit. The semi-variogram
values are calculated for pairs of residuals within the same group. If
collapse
is different from "none"
, the individual
semi-variogram values are collapsed using either a robust estimator
(robust = TRUE
) defined in Cressie (1993), or the average of
the values within the same distance interval. The semi-variogram is
useful for modeling the error term correlation structure.# S3 method for lme
Variogram(object, distance, form, resType, data,
na.action, maxDist, length.out, collapse, nint, breaks,
robust, metric, …)
"lme"
, representing
a fitted linear mixed-effects model.form
, data
, and
metric
, unless object
includes a corSpatial
element, in which case the associated covariate (obtained with the
getCovariate
method) is used.|
operator in
form
). Default is ~1
, implying that the observation
order within the groups is used to obtain the distances."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
. By default, the same data used to fit object
is used.NA
s. The default action (na.fail
) causes
an error message to be printed and the function to terminate, if there
are any incomplete observations.object
includes a corSpatial
element, its semi-variogram values are
calculated and this argument is used as the length.out
argument to the corresponding Variogram
method. Defaults to
50
."quantiles"
, the semi-variogram values are split
according to quantiles of the distance distribution, with equal
number of observations per group, with possibly varying distance
interval lengths. Else, if "fixed"
, the semi-variogram values
are divided according to distance intervals of equal lengths, with
possibly different number of observations per interval. Else, if
"none"
, no collapsing is used and the individual
semi-variogram values are returned. Defaults to "quantiles"
.20
.TRUE
the robust estimator is
used. Defaults to FALSE
.collapse
is
ignored."euclidean"
for the root sum-of-squares of distances;
"maximum"
for the maximum difference; and "manhattan"
for the sum of the absolute differences. Partial matching of
arguments is used, so only the first three characters need to be
provided. Defaults to "euclidean"
.variog
and dist
representing,
respectively, the semi-variogram values and the corresponding
distances. If the semi-variogram values are collapsed, an extra
column, n.pairs
, with the number of residual pairs used in each
semi-variogram calculation, is included in the returned data frame. If
object
includes a corSpatial
element, a data frame with
its corresponding semi-variogram is included in the returned value, as
an attribute "modelVariog"
. The returned value inherits from
class Variogram
.lme
,
Variogram
,
Variogram.default
,
Variogram.gls
,
plot.Variogram
fm1 <- lme(weight ~ Time * Diet, data=BodyWeight, ~ Time | Rat)
Variogram(fm1, form = ~ Time | Rat, nint = 10, robust = TRUE)
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