Summarize a gls Object

DESCRIPTION:

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.

USAGE:

summary(object, adjustSigma, verbose) 

REQUIRED ARGUMENTS:

object
an object inheriting from class gls, representing a generalized least squares fitted linear model.

OPTIONAL ARGUMENTS:

adjustSigma
an optional logical value. If TRUE and the estimation method used to obtain object was maximum likelihood, the standard errors of the coefficients are multiplied by sqrt(nobs/(nobs - npar)), with nobs and npar denoting, respectively, the number of observations and the number of coefficients. This converts the standard errors to REML-like estimates. Default is TRUE.
verbose
an optional logical value used to control the amount of output in the print.summary.gls method. Defaults to FALSE.

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 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 .

SEE ALSO:

, , ,

EXAMPLES:

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