summary.gls {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`. The returned object is suitable for printing with the `print.summary.gls` method.

### 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 in the `print.summary.gls` method. 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

`gls`, `AIC`, `BIC`, `print.summary.gls`

### Examples

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

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