Usage
Gls(model, data, correlation, weights, subset, method, na.action=na.omit,
control, verbose, B=0, dupCluster=FALSE, pr=FALSE,
opmeth=c('optimize','optim'), x=FALSE)## S3 method for class 'Gls':
print(x, digits=4, coefs=TRUE, latex=FALSE, \dots)
Arguments
model
a two-sided linear formula object describing the
model, with the response on the left of a ~ operator and the
terms, separated by + operators, on the right.
data
an optional data frame containing the variables named in
model, correlation, weights, and
subset. By default the variables are taken from the
environment from which gls is called.
correlation
an optional corStruct object describing the
within-group correlation structure. See the documentation of
corClasses for a description of the available corStruct
classes. If a grouping variable is to be used,
weights
an optional varFunc object or one-sided formula
describing the within-group heteroscedasticity structure. If given as
a formula, it is used as the argument to varFixed,
corresponding to fixed variance weights. See the do
subset
an optional expression indicating which subset of the rows of
data should be used in the fit. This can be a logical
vector, or a numeric vector indicating which observation numbers are
to be included, or a character vector of the
method
a character string. If "REML" the model is fit by
maximizing the restricted log-likelihood. If "ML" the
log-likelihood is maximized. Defaults to "REML".
na.action
a function that indicates what should happen when the
data contain NAs. The default action (na.omit) results
in deletion of observations having any of the variables of interest missing.
control
a list of control values for the estimation algorithm to
replace the default values returned by the function glsControl.
Defaults to an empty list.
verbose
an optional logical value. If TRUE information on
the evolution of the iterative algorithm is printed. Default is
FALSE.
B
number of bootstrap resamples to fit and store, default is
none
dupCluster
set to TRUE to have Gls when
bootstrapping to consider multiply-sampled clusters as if they were
one large cluster when fitting using the gls algorithm
pr
set to TRUE to show progress of bootstrap resampling
opmeth
specifies whether the optimize or the optim
function is to be used for optimization
x
for Gls set to TRUE to store the design matrix
in the fit object; otherwise the result of Gls
digits
number of significant digits to print
coefs
specify coefs=FALSE to suppress printing the table
of model coefficients, standard errors, etc. Specify coefs=n
to print only the first n regression coefficients in the
model.
latex
a logical value indicating whether information should be
formatted as plain text or as LaTeX markup