lm.gls {MASS}R Documentation

Fit Linear Models by Generalized Least Squares


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 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.


The problem is transformed to uncorrelated form and passed 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.

See Also

gls, lm, lm.ridge

[Package MASS version 7.2-23 Index]