RESEARCH ARTICLE
A Note on the Maximum Likelihood Estimators for the Mixture of Maxwell Distributions Using Type-I Censored Scheme
Syed Mohsin Ali Kazmia, *, Muhammad Aslamb, Sajid Alib
Article Information
Identifiers and Pagination:
Year: 2011Volume: 3
First Page: 31
Last Page: 35
Publisher Id: TOSPJ-3-31
DOI: 10.2174/1876527001103010031
Article History:
Received Date: 2/9/2011Revision Received Date: 12/10/2011
Acceptance Date: 18/10/2011
Electronic publication date: 23/12/2011
Collection year: 2011
© 2011 Mohsin Ali Kazmi et al.;
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
This article focuses on the study of mixture density under Type I censoring scheme by taking Maxwell distribution as a life time model. In this paper we sculpt a heterogeneous population by means of two components mixture of the Maxwell distribution. We derive the maximum likelihood estimators using type-I censored data and also their variances matrix. The problem with ML estimators is discussed. The Maple 13.0 code is also presented in appendix.
Keywords: Finite mixture of Maxwell distribution, Censored sampling, Fixed termination time, ML..
