BIC_model_choice: BIC_model_choice

In pmgrollemund/bliss: Bayesian Functional Linear Regression with Sparse Step Functions

BIC_model_choice

Description

Model selection with BIC criterion.

Usage

BIC_model_choice(Ks, iter, data, verbose = T)

Arguments

Ks	a numerical vector containing the K values.
iter	an integer, the number of iteration for each run of fit_Bliss.
data	a list containing required options to run the function fit_Bliss.
verbose	write stuff if TRUE (optional).

Value

A numerical vector, the BIC values for the Bliss model for different K value.

Examples

param_sim <- list(Q=1,n=100,p=c(50),grids_lim=list(c(0,1)))
data      <- sim(param_sim,verbose=TRUE)
iter = 1e2
Ks <- 1:5

res_BIC <- BIC_model_choice(Ks,iter,data)
plot(res_BIC,xlab="K",ylab="BIC")

pmgrollemund/bliss documentation built on July 15, 2024, 5:02 p.m.