MASS: lm.gls – R documentation

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MASS

lm.gls

Fit Linear Models by Generalized Least Squares

Description

Fit linear models by Generalized Least Squares

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, 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.