Statistical estimation for the parameters of Weibull distribution based on progressively type-I interval censored sample

Hon Keung Tony Ng, Zhu Wang

Research output: Contribution to journalArticlepeer-review

47 Scopus citations

Abstract

In this paper, the estimation of parameters based on a progressively type-I interval censored sample from a two-parameter Weibull distribution is studied. Different methods of estimation are discussed. They include the maximum likelihood estimation, method of moments, estimation based on Weibull probability plot, mid-point approximation method and one-step approximation method. The estimation procedures are discussed in details and compared via Monte Carlo simulations in terms of their biases and mean square errors. Some recommendations are made from the simulation results and a numerical example is presented to illustrate all of the methods of estimation developed here.

Original languageEnglish (US)
Pages (from-to)145-159
Number of pages15
JournalJournal of Statistical Computation and Simulation
Volume79
Issue number2
DOIs
StatePublished - Feb 2009
Externally publishedYes

Keywords

  • EM algorithm
  • Grouped data
  • Lifetime data
  • Maximum likelihood estimation
  • Method of moments

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Statistical estimation for the parameters of Weibull distribution based on progressively type-I interval censored sample'. Together they form a unique fingerprint.

Cite this