An object returned by the
gls function, inheriting from class
"gls" and representing a generalized least squares fitted linear
model. Objects of this class have methods for the generic functions
The following components must be included in a legitimate
an approximate covariance matrix for the
variance-covariance coefficients. If
apVar = FALSE in the list
of control values used in the call to
component is equal to
a list containing an image of the
gls call that
produced the object.
a vector with the estimated linear model coefficients.
a list of the contrast matrices used to represent factors in the model formula. This information is important for making predictions from a new data frame in which not all levels of the original factors are observed. If no factors are used in the model, this component will be an empty list.
a list with basic dimensions used in the model fit,
including the components
N - the number of observations in
the data and
p - the number of coefficients in the linear
a vector with the fitted values.
an object inheriting from class
representing a list of linear model components, such as
a vector with the correlation structure grouping factor, if any is present.
the log-likelihood at convergence.
the estimation method: either
"ML" for maximum
"REML" for restricted maximum likelihood.
the number of iterations used in the iterative algorithm.
a vector with the residuals.
the estimated residual standard error.
an approximate covariance matrix of the coefficients estimates.