Improvement of expectation–maximization algorithm for phase‐type distributions with grouped and truncated data

DOI10.1002/asmb.1919OpenAlexW2129165987MaRDI QIDQ5414531

Tadashi Dohi, Hiroyuki Okamura, Kishor S. Trivedi

Publication date: 6 May 2014

Published in: Applied Stochastic Models in Business and Industry (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/asmb.1919

zbMATH Keywords

parameter estimationEM algorithmmaximum likelihood estimationphase-type distributiongrouped and truncated data

Mathematics Subject Classification ID

Software, source code, etc. for problems pertaining to statistics (62-04) Statistical distribution theory (62Exx)

Related Items (4)

Phase-type software reliability model: parameter estimation algorithms with grouped data ⋮ Multiplicative background risk models: setting a course for the idiosyncratic risk factors distributed phase-type ⋮ Fitting discrete phase-type distribution from censored and truncated observations with pre-specified hazard sequence ⋮ A uniformisation-driven algorithm for inference-related estimation of a phase-type ageing model

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Large Sample Properties of Generalized Method of Moments Estimators
• A fully Bayesian approach to inference for Coxian phase-type distributions with covariate dependent mean
• Bayesian prediction of the transient behaviour and busy period in short- and long-tailed GI/G/1 queueing systems
• On the convergence properties of the EM algorithm
• Numerical transient analysis of Markov models
• Bayesian estimation for the \(M\)/\(G\)/1 queue using a phase-type approximation
• An Algorithm for Computing Minimal% Coxian Representations
• On optimal and data-based histograms
• On a Possibilistic Approach to the Analysis of Fuzzy Feedback Systems
• On the Three-Moment Approximation of a General Distribution by a Coxian Distribution
• Fitting Mixture Models to Grouped and Truncated Data via the EM Algorithm
• Matching moments to phase distributions: density function shapes
• Selecting Parameters of Phase Distributions: Combining Nonlinear Programming, Heuristics, and Erlang Distributions
• A benchmark for ph estimation algorithms: results for acyclic-ph
• Moment matching using a family of phase-type distributions
• Matching moments to phase distributions: Mixtures of erlang distributions of common order
• Matching Three Moments with Minimal Acyclic Phase Type Distributions
• The estimation of phase-type related functionals using Markov chain Monte Carlo methods

This page was built for publication: Improvement of expectation–maximization algorithm for phase‐type distributions with grouped and truncated data