summary.reaster {aster}

Summarizing Aster Model with Random Effects Fits

Description

These functions are all methods for class reaster or summary.reaster objects.

Usage

## S3 method for class 'reaster'
summary(object, standard.deviation = TRUE, ...)

## S3 method for class 'summary.reaster'
print(x, digits = max(3, getOption("digits") - 3),
      signif.stars = getOption("show.signif.stars"), ...)

Arguments

object

an object of class "reaster", usually, a result of a call to reaster.

standard.deviation

if TRUE, treat the parameters described in the “variance components” section of the printout are square roots of variance components (that is, standard deviations) rather than the variance components themselves. Warning: if FALSE so actual variance components are described, (asymptotic, approximate) standard errors are zero when they the variance components are zero (see details section below).

x

an object of class "summary.reaster", usually, a result of a call to summary.reaster.

digits

the number of significant digits to use when printing.

signif.stars

logical. If TRUE, “significance stars” are printed for each coefficient.

...

further arguments passed to or from other methods.

Details

The reaster function only does approximate maximum likelihood. Even if it did actual maximum likelihood, standard errors would be only approximate. Standard errors for variance components are derived via the delta method from standard errors for square roots of variance components (standard deviations). Hence P-values for variance components and square roots of variance components do not agree exactly (although they do asymptotically).

Value

summary.reaster returns an object of class "summary.reaster".

See Also

reaster, summary.