dfpBayLasSte: Performs one iteration of DFP for the Bayesian Lasso

In Rene-Gutierrez/DynParRegReg:

Description

This function performs one step of the DFP with the Bayesian Lasso prior. The inputs are described in Algorithm 1 and the Supplementary Materials of Guhaniyogi & Gutierrez.

Usage

dfpBayLasSte(P, XX, Xy, yy, sN, hb, hs, hl, ht, hlsc, hlsh, nmcmc)

Arguments

P	Current partition to be used.
XX	Sufficient statistic X'X.
Xy	Sufficient statistic X'y.
yy	Sufficient statistic y'y.
sN	Number of Observations.
hb	Point estimate of the coefficients.
hs	Point estimates of the variance of the error.
hl	Point estimate for the global shrinking parameter.
ht	Point estimate for the local shrinking parameters.
hlsc	Hyper-prior for the lambda parameter rate.
hlsh	Hyper-prior for the lambda parameter shape.
nmcmc	Number of samples of the parameters.

Value

A list containing samples for the model parameters.

sb

A matrix with samples for coefficients, 1 sample per row.

st

A matrix with samples for local shrinkage parameters, 1 sample per row.

ss

Samples for sigma.

sl

Samples for the global shrinkage parameter.

Author(s)

Rene Gutierrez Marquez

Rene-Gutierrez/DynParRegReg documentation built on Dec. 18, 2021, 9:57 a.m.