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 = F, method = "qr",
model = F, x = F, y = F, contrasts = NULL, ...)
REQUIRED ARGUMENTS:
- formula
-
a formula expression as for regression models, of the form
response ~ predictors
.
See the documentation of
formula
for other details.
OPTIONAL ARGUMENTS:
- 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
.
VALUE:
An object of class
"lm"
, with additional
class
"lm.gls"
DETAILS:
The problem is transformed to uncorrelated form and passed to
lm.fit
.
SEE ALSO:
,
,
,