summary.gls               package:nlme               R Documentation

Summarize a 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 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'.

Author(s):

     Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates
     bates@stat.wisc.edu

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)

