Summarize a Generalized Least Squares 'gls' Object

summary.gls {nlme}

R Documentation

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 class '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`.

Author(s)

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

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"

[Package nlme version 3.1-139 Index]

Summarize a Generalized Least Squares gls Object