| lm.gls {MASS} | R Documentation |
Fit linear models by Generalized Least Squares
lm.gls(formula, data, W, subset, na.action, inverse = FALSE,
method = "qr", model = FALSE, x = FALSE, y = FALSE,
contrasts = NULL, ...)
formula |
a formula expression as for regression models, of the form
response ~ predictors.
See the documentation of formula for other details.
|
data |
an optional data frame in which to interpret the variables occurring
in formula.
|
W |
a weight matrix. |
subset |
expression saying which subset of the rows of the data should be used in the fit. All observations are included by default. |
na.action |
a function to filter missing data. |
inverse |
logical: if true W specifies the inverse of the weight matrix: this
is appropriate if a variance matrix is used.
|
method |
method to be used by lm.fit.
|
model |
should the model frame be returned? |
x |
should the design matrix be returned? |
y |
should the response be returned? |
contrasts |
a list of contrasts to be used for some or all of |
... |
additional arguments to lm.fit.
|
The problem is transformed to uncorrelated form and passed to
lm.fit.
An object of class "lm.gls", which is similar to an "lm"
object. There is no "weights" component, and only a few "lm"
methods will work correctly. As from version 7.1-22 the residuals and
fitted values refer to the untransformed problem.