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.

a list containing an image of the gls call that produced the object.

a vector with the estimated linear model coefficients.

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.

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.

a vector with the fitted values..

an object inheriting from class glsStruct, representing a list of linear model components, such as corStruct and varFunc objects.

a vector with the correlation structure grouping factor, if any is present.

the log-likelihood at convergence.

the estimation method: either "ML" for maximum likelihood, or "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.