lm.gls
Fit Linear Models by Generalized Least Squares
Fit linear models by Generalized Least Squares
- Keywords
- models
Usage
lm.gls(formula, data, W, subset, na.action, inverse = FALSE,
method = "qr", model = FALSE, x = FALSE, y = FALSE,
contrasts = NULL, …)
Arguments
- formula
a formula expression as for regression models, of the form
response ~ predictors
. See the documentation offormula
for other details.- data
an optional data frame, list or environment 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
.
Details
The problem is transformed to uncorrelated form and passed to
lm.fit
.
Value
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.