nlme (version 3.1-131)

summary.gls: Summarize a Generalized Least Squares

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, …)

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.

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.

See Also

AIC, BIC, gls, summary

Examples

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