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 offormulafor 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
Wspecifies 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.