x components are obtained. The 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).
"plot"(x, form, abline, id, idLabels, grid, ...)"lmList", representing
a list of lm objects with a common 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 = "pool") ~ fitted(.) ,
corresponding to a plot of the standardized residuals (using a pooled
estimate for the residual standard error) versus fitted values.
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 getGroups(x).
xyplot defaults to TRUE, else defaults to
FALSE.
lmList,predict.lm,
xyplot, bwplot, histogram
fm1 <- lmList(distance ~ age | Subject, Orthodont)
# standardized residuals versus fitted values by gender
plot(fm1, resid(., type = "pool") ~ fitted(.) | Sex, abline = 0, id = 0.05)
# 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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