Results 91 to 100 of about 5,420,390 (236)

Efficient identification of parameter space structure with Modified Metropolis-Hastings algorithm [PDF]

, 2023
Adriana T. Dawes, Natalia Kravtsova, Helen Chamberlin   +2 more
openalex   +1 more source

A Note on the Cowles-EM Algorithm for Bayesian Ordinal Probit Models

Research in Statistics
We describe a novel procedure for Bayesian cutpoint simulation in ordered probit models. Our approach capitalizes upon a series of auxiliary binary probit models implied by the ordinal probit to craft tailored proposal distributions for Metropolis ...
Justin L. Tobias
doaj   +1 more source

Fully Bayesian Estimation of Simultaneous Regression Quantiles under Asymmetric Laplace Distribution Specification

Journal of Probability and Statistics, 2019
In this paper, we are interested in estimating several quantiles simultaneously in a regression context via the Bayesian approach. Assuming that the error term has an asymmetric Laplace distribution and using the relation between two distinct quantiles ...
Josephine Merhi Bleik
doaj   +1 more source

Optimal proposal distributions and adaptive MCMC [PDF]

. We review recent work concerning optimal proposal scalings for Metropolis-Hastings MCMC algorithms, and adaptive MCMC algorithms for trying to improve the algorithm on the fly. 1. Introduction. The Metropolis-Hastings algorithm (Metropolis et al., 1953;
A. Gelman, Chapter For Mcmc H, G. Jones, Jeffrey S. Rosenthal, S. Brooks, X. -l. Meng   +5 more
core  

On the flexibility of the design of Multiple Try Metropolis schemes

, 2013
The Multiple Try Metropolis (MTM) method is a generalization of the classical Metropolis-Hastings algorithm in which the next state of the chain is chosen among a set of samples, according to normalized weights. In the literature, several extensions have
A Mira, AA Barker, CP Robert, D Frenkel, D Gamerman, G Storvik, GO Roberts, H Haario, H Haario, Jesse Read, JS Liu, JS Liu, L Devroye, L Martino, L Tierney, L Tierney, Luca Martino, M Bédard, N Metropolis, PH Peskun, RV Craiu, SP Brooks, WJ Fitzgerald, WK Hastings, WR Gilks, ZS Qin   +25 more
core   +1 more source

Stochastic block models: A comparison of variants and inference methods.

PLoS ONE, 2019
Finding communities in complex networks is a challenging task and one promising approach is the Stochastic Block Model (SBM). But the influences from various fields led to a diversity of variants and inference methods.
Thorben Funke, Till Becker
doaj   +1 more source

Optimal scaling for partially updating MCMC algorithms

, 2006
In this paper we shall consider optimal scaling problems for high-dimensional Metropolis--Hastings algorithms where updates can be chosen to be lower dimensional than the target density itself.
Neal, Peter, Roberts, Gareth
core   +2 more sources

Approximate Bayesian Credible Intervals for the Parameters of the Gompertz Distribution with Failure Censored Data

Journal of Statistical Theory and Applications (JSTA)
We considered Bayesian interval estimation for the parameters of the Gompertz distribution with failure-censored data. We derived credible intervals for the shape and scale parameters using the Metropolis–Hastings algorithm and higher-order asymptotic ...
Ayman Baklizi
doaj   +1 more source

Bayesian Inference from Composite Likelihoods, with an Application to Spatial Extremes [PDF]

, 2011
Composite likelihoods are increasingly used in applications where the full likelihood is analytically unknown or computationally prohibitive. Although the maximum composite likelihood estimator has frequentist properties akin to those of the usual ...
Cooley, Daniel, Davison, Anthony C., Ribatet, Mathieu   +2 more
core  

Bayesian and Classical Estimation of Stress-Strength Reliability for Inverse Weibull Lifetime Models

Algorithms, 2017
In this paper, we consider the problem of estimating stress-strength reliability for inverse Weibull lifetime models having the same shape parameters but different scale parameters.
Qixuan Bi, Wenhao Gui
doaj   +1 more source