| lmList {nlme} | R Documentation |
Data is partitioned according to the levels of the grouping
factor g and individual lm fits are obtained for each
data partition, using the model defined in object.
lmList(object, data, level, subset, na.action, pool) ## S3 method for class 'lmList' update(object, formula., ..., evaluate = TRUE) ## S3 method for class 'lmList' print(x, pool, ...)
object |
For |
formula |
(used in |
formula. |
Changes to the formula – see |
data |
a data frame in which to interpret the variables named in
|
level |
an optional integer specifying the level of grouping to be used when multiple nested levels of grouping are present. |
subset |
an optional expression indicating which subset of the rows of
|
na.action |
a function that indicates what should happen when the
data contain |
pool |
an optional logical value indicating whether a pooled estimate of the residual standard error should be used in calculations of standard deviations or standard errors for summaries. |
x |
an object inheriting from class |
... |
some methods for this generic require additional arguments. None are used in this method. |
evaluate |
If |
a list of lm objects with as many components as the number of
groups defined by the grouping factor. Generic functions such as
coef, fixed.effects, lme, pairs,
plot, predict, random.effects, summary,
and update have methods that can be applied to an lmList
object.
Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models in S and S-PLUS", Springer.
lm,
lme.lmList,
plot.lmList,
pooledSD,
predict.lmList,
residuals.lmList,
summary.lmList
fm1 <- lmList(distance ~ age | Subject, Orthodont) summary(fm1)