On Gibbs Sampling for Structured Bayesian Models Discussion of paper by Zanella and Roberts

12/16/2021
by   Xiaodong Yang, et al.
0

This article is a discussion of Zanella and Roberts' paper: Multilevel linear models, gibbs samplers and multigrid decompositions. We consider several extensions in which the multigrid decomposition would bring us interesting insights, including vector hierarchical models, linear mixed effects models and partial centering parametrizations.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/19/2021

Scalable computation for Bayesian hierarchical models

The article is about algorithms for learning Bayesian hierarchical model...
research
10/20/2021

A Gentle Introduction to Bayesian Hierarchical Linear Regression Models

Considering the flexibility and applicability of Bayesian modeling, in t...
research
04/06/2021

Discussion of "A Gibbs sampler for a class of random convex polytopes"

An exciting new algorithmic breakthrough has been advanced for how to ca...
research
09/01/2020

Multilevel decompositions and norms for negative order Sobolev spaces

We consider multilevel decompositions of piecewise constants on simplici...
research
04/14/2023

Complexity of Gibbs samplers through Bayesian asymptotics

Gibbs samplers are popular algorithms to approximate posterior distribut...
research
09/17/2022

Geometric ergodicity of Gibbs samplers for Bayesian error-in-variable regression

We consider Bayesian error-in-variable (EIV) linear regression accountin...
research
05/03/2018

A Coefficient of Determination (R2) for Linear Mixed Models

Extensions of linear models are very commonly used in the analysis of bi...

Please sign up or login with your details

Forgot password? Click here to reset