gamselBayesUpdate {gamselBayes}

Update a gamselBayes() fit object.

Description

Facilitates updating of gamselBayes fit object when two key parameters controlling model selection are modified. Use of gamselBayesUpdate() allows for fast tweaking of such parameters without another, potentially time-consuming, call to gamselBayes().

Usage

gamselBayesUpdate(fitObject,lowerMakesSparser = NULL)

Arguments

fitObject

gamselBayes() fit object.

lowerMakesSparser

A threshold parameter between 0 and 1, which is such that lower values lead to sparser fits.

Details

The gamselBayesUpdate() function is applicable when a gamselBayes() fit object has been obtained for particular data inputs y, Xlinear and Xgeneral (as well as other tuning-type inputs) and the analyst is interested in changing the value of the parameter that controls model selection. This parameter is named lowerMakesSparser, and is described above. A call to gamselBayesUpdate() with a new value of lowerMakesSparse produces an updated gamselBayes() fit object with, potentially, different effect type estimates.

Value

An object of class gamselBayes with the same components as those produced by the gamselBayes() function. See help(gamselBayes) for details.

Author(s)

Virginia X. He [e-mail] and Matt P. Wand [e-mail]

Examples

 
library(gamselBayes) 

# Generate some regression-type data:

set.seed(1) ;  n <- 5000  ; numPred <- 15
Xgeneral <- as.data.frame(matrix(runif(n*numPred),n,numPred))
names(Xgeneral) <- paste("x",1:numPred,sep="")

y <- as.vector(0.1 + 0.4*Xgeneral[,1] - 2*pnorm(3-6*Xgeneral[,2]) 
               - 0.9*Xgeneral[,4] + cos(3*pi*Xgeneral[,5]) + 2*rnorm(n))

# Obtain and assess a gamselBayes() fit:

fitOrig <- gamselBayes(y,Xgeneral = Xgeneral)
summary(fitOrig) ; plot(fitOrig)
print(fitOrig$effectTypesHat)

# Update the gamselBayes() fit object with a new value of 
# the "lowerMakesSparser" parameter:

fitUpdated <-  gamselBayesUpdate(fitOrig,lowerMakesSparser = 0.6)
summary(fitUpdated) ; plot(fitUpdated)
print(fitUpdated$effectTypesHat)