# lm.gls

0th

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##### 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 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.
##### 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.

gls, lm, lm.ridge