summary.zlm: Summarizing Linear Models under Zellner's g

In BMS: Bayesian Model Averaging Library

Summarizing Linear Models under Zellner's g

Description

summary method for class "zlm"

Usage

## S3 method for class 'zlm'
summary(object, printout = TRUE, ...)

Arguments

object	an object of class zlm: see "Examples" below
printout	If TRUE (default, then information is printed to console in a neat form
...	further arguments passed to or from other methods

Details

summary.zlm prints out coefficients expected values and their standard deviations, as well as information on the gprior and the log marginal likelihood. However, it invisibly returns a list with elements as described below:

Value

A list with the following elements

residuals	The expected value of residuals from the model
coefficients	The posterior expected values of coefficients (including the intercept)
coef.sd	Posterior standard deviations of the coefficients (the intercept SD is NA, since an improper prior was used)
gprior	The g prior as it has been submitted to object
E.shrinkage	the shrinkage factor g/(1+g), respectively its posterior expected value in case of a hyper-g prior
SD.shrinkage	(Optionally) the shrinkage factor's posterior standard deviation (in case of a hyper-g prior)
log.lik	The log marginal likelihood of the model

Author(s)

Stefan Zeugner

See Also

zlm for creating zlm objects, link{summary.lm} for a similar function on OLS models

See also http://bms.zeugner.eu for additional help.

Examples

data(datafls)

#simple example
foo = zlm(datafls)
summary(foo)

sfoo = summary(foo,printout=FALSE)
print(sfoo$E.shrinkage)

BMS documentation built on Aug. 9, 2022, 5:08 p.m.