| summary.gls {nlme} | R Documentation |
Additional information about the linear model fit represented
by object is extracted and included as components of
object. The returned object is suitable for printing with the
print.summary.gls method.
summary(object, verbose)
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 in the print.summary.gls method. Defaults to
FALSE. |
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 data frame 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. |
Jose Pinheiro and Douglas Bates
gls, AIC, BIC,
print.summary.gls
data(Ovary)
fm1 <- gls(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), Ovary,
correlation = corAR1(form = ~ 1 | Mare))
summary(fm1)