| 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.
## S3 method for class 'gls': 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. |
... |
some methods for this generic require additional arguments. None are used in this method. |
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 Jose.Pinheiro@pharma.novartis.com and Douglas Bates bates@stat.wisc.edu
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)