Bayes and Non-Bayes Estimation of Change Point in Nonstandard Mixture Inverse Weibull Distribution

DOI

10.2991/jsta.d.190306.011How to use a DOI?

Keywords

Bayes estimate; change point; mixture distribution; inverse Weibull distribution; maximum likelihood estimate

Abstract

We consider a sequence of independent random variables X1,X2,…,Xm,…,Xnn≥3 exhibiting a change in the probability distribution of the data generating mechanism. We suppose that the distribution changes at some point, called a change point, to a second distribution for the remaining observations. We propose Bayes estimators of change point under symmetric loss functions and asymmetric loss functions. The sensitivity analysis of Bayes estimators are carried out by simulation and numerical comparisons with R-programming.

Copyright

© 2019 The Authors. Published by Atlantis Press SARL.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Masoud Ganji
AU  - Roghayeh Mostafayi
PY  - 2019
DA  - 2019/03/31
TI  - Bayes and Non-Bayes Estimation of Change Point in Nonstandard Mixture Inverse Weibull Distribution
JO  - Journal of Statistical Theory and Applications
SP  - 79
EP  - 86
VL  - 18
IS  - 1
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.d.190306.011
DO  - 10.2991/jsta.d.190306.011
ID  - Ganji2019
ER  -