summary.fusion: Summary of object of class 'fusion'

In effectFusion: Bayesian Effect Fusion for Categorical Predictors

Description

Returns basic information about the model and the priors, MCMC details and posterior means from the refit of the selected model or model averaged results as well as 95%-HPD intervals for the regression effects.

Usage

## S3 method for class 'fusion'
summary(object, ...)

Arguments

object	an object of class fusion
...	further arguments passed to or from other methods (not used)

Details

The model selected with function effectFusion is refitted with a flat uninformative prior to get estimates for the regression coefficients beta. The posterior means and 95%-HPD intervals resulting from this refit are shown with this function. Fused categories have the same regression coefficient estimates and the same HPD intervals.

If a full model is fitted (method in effectFusion is NULL) or no final model selection is performed (argument modelSelection in effectFusion is NULL), the coefficient estimates are model averaged results.

Author(s)

Daniela Pauger, Magdalena Leitner <[e-mail]>

See Also

effectFusion

Examples

## see example for effectFusion

Example output

effectFusion documentation built on Oct. 14, 2021, 1:07 a.m.