# 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 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.

##### See Also

*Documentation reproduced from package MASS, version 7.3-51.1, License: GPL-2 | GPL-3*