form
argument gives considerable flexibility in the type of
plot specification. A conditioning expression (on the right side of a
|
operator) always implies that different panels are used for
each level of the conditioning factor, according to a Trellis
display. If form
is a one-sided formula, histograms of the
variable on the right hand side of the formula, before a |
operator, are displayed (the Trellis function histogram
is
used). If form
is two-sided and both its left and
right hand side variables are numeric, scatter plots are displayed
(the Trellis function xyplot
is used). Finally, if form
is two-sided and its left had side variable is a factor, box-plots of
the right hand side variable by the levels of the left hand side
variable are displayed (the Trellis function bwplot
is used).# S3 method for lme
plot(x, form, abline, id, idLabels, idResType, grid, …)
# S3 method for nls
plot(x, form, abline, id, idLabels, idResType, grid, …)
"lme"
, representing
a fitted linear mixed-effects model, or from nls
, representing
an fitted nonlinear least squares model.x
can be referenced. In addition, x
itself
can be referenced in the formula using the symbol
"."
. Conditional expressions on the right of a |
operator can be used to define separate panels in a Trellis
display. Default is resid(., type = "p") ~ fitted(.)
,
corresponding to a plot of the standardized residuals versus fitted
values, both evaluated at the innermost level of nesting.idLabels
. If given as a one-sided
formula, its right hand side must evaluate to a logical, integer, or
character vector which is used to identify observations in the
plot. If missing, no observations are identified.id
. If given as a
one-sided formula, its right hand side must evaluate to a vector
which is converted to character and used to label the identified
observations. Default is the innermost grouping factor.id
is a
numeric value. 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"
.xyplot
defaults to TRUE
, else defaults to
FALSE
.lme
, xyplot
,
bwplot
, histogram
fm1 <- lme(distance ~ age, Orthodont, random = ~ age | Subject)
# standardized residuals versus fitted values by gender
plot(fm1, resid(., type = "p") ~ fitted(.) | Sex, abline = 0)
# box-plots of residuals by Subject
plot(fm1, Subject ~ resid(.))
# observed versus fitted values by Subject
plot(fm1, distance ~ fitted(.) | Subject, abline = c(0,1))
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