Fitted gls Object

DESCRIPTION:

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 anova , coef, fitted, formula, getGroups , getResponse, intervals, logLik, plot , predict, print, residuals, summary , and update.

VALUE:

The following components must be included in a legitimate gls object.
apVar
an approximate covariance matrix for the variance-covariance coefficients. If apVar = FALSE in the list of control values used in the call to gls, this component is equal to NULL.
call
a list containing an image of the gls call that produced the object.
coefficients
a vector with the estimated linear model coefficients.
contrasts
a list with the contrasts 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.
dims
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 model.
fitted
a vector with the fitted values..
glsStruct
an object inheriting from class glsStruct, representing a list of linear model components, such as corStruct and varFunc objects.
groups
a vector with the correlation structure grouping factor, if any is present.
logLik
the log-likelihood at convergence.
method
the estimation method: either "ML" for maximum likelihood, or "REML" for restricted maximum likelihood.
numIter
the number of iterations used in the iterative algorithm.
residuals
a vector with the residuals.
sigma
the estimated residual standard error.
varBeta
an approximate covariance matrix of the coefficients estimates.

SEE ALSO:

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