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, 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`

.

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.

The problem is transformed to uncorrelated form and passed to
`lm.fit`

.