A Metropolis version of the EM algorithm
نویسندگان
چکیده
The Expectation Maximisation (EM) algorithm is a popular technique for maximum likelihood in incomplete data models. In order to overcome its documented limitations, several stochastic variants are proposed in the literature. However, none of these algorithms is guaranteed to provide a global maximizer of the likelihood function. In this paper we introduce the MEM algorithm — a Metropolis version of the EM — that can achieve global maximisation of the likelihood.
منابع مشابه
Convergence of the Monte Carlo Em for Curved Exponential Families
SUMMARY The Monte Carlo Expectation Maximization (MCEM) algorithm (Wei and Tanner (1991)), a stochas-tic version of EM, is a versatile tool for inference in incomplete data models, especially when used in combination with MCMC simulation methods. Examples of applications include, among many others: regression with missing values (Wei and Tanner (1991)), time-series analysis (Chan and Ledolter (...
متن کاملFinite mixture models for exponential repeated data
The analysis of finite mixture models for exponential repeated data is considered. The mixture components correspond to different possible states of the statistical units. Dependency and variability of repeated data are taken into account through random effects. For each component, an exponential mixed model is thus defined. When considering parameter estimation in this mixture of exponential m...
متن کاملClass Notes: Methods to Map QTL Contents
1 Basic Concepts 2 1.1 Terminology and Definitions . . . . . . . . . . . . . . . . . . . . . 2 1.2 Hardy-Weinberg Equilibrium . . . . . . . . . . . . . . . . . . . . 2 1.3 Gametic Equilibrium . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.4 Crossingover and Recombination . . . . . . . . . . . . . . . . . . 3 1.5 Interference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1...
متن کاملJa n 20 04 Analysis of systematic scan Metropolis algorithms using Iwahori - Hecke algebra techniques
We give the first analysis of a systematic scan version of the Metropolis algorithm. Our examples include generating random elements of a Coxeter group with probability determined by the length function. The analysis is based on interpreting Metropolis walks in terms of the multiplication in the Iwahori-Hecke algebra.
متن کاملAnalysis of systematic scan Metropolis algorithms using Iwahori - Hecke algebra techniques
We give the first analysis of a systematic scan version of the Metropolis algorithm. Our examples include generating random elements of a Coxeter group with probability determined by the length function. The analysis is based on interpreting Metropolis walks in terms of the multiplication in the Iwahori-Hecke algebra.
متن کامل