summary.gls: Summarize a Generalized Least Squares `gls` Object

Description

Additional information about the linear model fit represented by object is extracted and included as components of object.

Usage

# S3 method for gls
summary(object, verbose, ...)

Value

an object inheriting from class summary.gls with all components included in object (see glsObject for a full description of the components) plus the following components:

corBeta: approximate correlation matrix for the coefficients estimates
tTable: a matrix with columns Value, Std. Error, t-value, and p-value representing respectively the coefficients estimates, their approximate standard errors, the ratios between the estimates and their standard errors, and the associated p-value under a \(t\) approximation. Rows correspond to the different coefficients.
residuals: if more than five observations are used in the gls fit, a vector with the minimum, first quartile, median, third quartile, and maximum of the residuals distribution; else the residuals.
AIC: the Akaike Information Criterion corresponding to object.
BIC: the Bayesian Information Criterion corresponding to object.

Arguments

object: an object inheriting from class "gls", representing a generalized least squares fitted linear model.
verbose: an optional logical value used to control the amount of output when the object is printed. Defaults to FALSE.
...: some methods for this generic require additional arguments. None are used in this method.

Author

José Pinheiro and Douglas Bates bates@stat.wisc.edu

Examples

Run this code

fm1 <- gls(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), Ovary,
           correlation = corAR1(form = ~ 1 | Mare))
summary(fm1)
coef(summary(fm1)) # "the matrix"

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