Drug risk assessment with determining the number of sub-populations under finite mixture normal models
type: Item
instance of: scholarly article
title: Drug risk assessment with determining the number of sub-populations under finite mixture normal models
zbMATH Open document ID: 1429.62615
author: Jian Tao
author: Sik Lee
author: Ning-Zhong Shi
published in: Computational Statistics and Data Analysis
publication date: 2008-11-26T00:00:00Z
Mathematics Subject Classification ID: 62P10
Mathematics Subject Classification ID: 62F15
zbMATH DE Number: 5374029
zbMATH Keywords: Bayes factor
zbMATH Keywords: BIC
zbMATH Keywords: dose-response
zbMATH Keywords: EM algorithm
zbMATH Keywords: mixture normal models
zbMATH Keywords: model selection
zbMATH Keywords: risk assessment
zbMATH Keywords: Schwarz criterion
describes a project that uses: Matlab
MaRDI profile type: Publication
full work available at URL: j.csda.2003.09.006
OpenAlex ID: W2081514374
cites work: Q3696308
cites work: Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models
cites work: Editorial: Recent developments in mixture models (Hamburg, July 2001)
cites work: Benchmark Dose Calculation from Epidemiological Data
cites work: Q4845386
cites work: Marginal Likelihood from the Gibbs Output
cites work: Marginal Likelihood From the Metropolis–Hastings Output
cites work: Q4139463
cites work: Computing Bayes Factors by Combining Simulation and Asymptotic Approximations
cites work: On Bartlett adjustments for approximate Bayesian inference
cites work: Bayesian Density Estimation and Inference Using Mixtures
cites work: Q4298922
cites work: Simulating normalizing constants: From importance sampling to bridge sampling to path sampling
cites work: Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
cites work: Choosing initial values for the EM algorithm for finite mixtures
cites work: Bayes Factors
cites work: Fitting of mixtures with unspecified number of components using cross validation distance estimate
cites work: Risk Assessment for Quantitative Responses Using a Mixture Model
cites work: Mixture Densities, Maximum Likelihood and the EM Algorithm
cites work: Practical Bayesian Density Estimation Using Mixtures of Normals
cites work: Estimating the dimension of a model
cites work: A Bayesian model selection method with applications
cites work: Accurate Approximations for Posterior Moments and Marginal Densities
cites work: Testing for outliers from a mixture distribution when some data are missing
DOI: 10.1016/J.CSDA.2003.09.006
description: scientific article; zbMATH DE number 5374029