Different methods of estimation in two parameter Geometric distribution with randomly censored data

2021 ◽  
Author(s):  
Neha Goel ◽  
Hare Krishna
Keyword(s):  
Censored Data ◽  
Geometric Distribution ◽  
Randomly Censored Data ◽  
Two Parameter ◽  
Randomly Censored

scholarly journals Maximum Likelihood and Bayes Estimation in Randomly Censored Geometric Distribution

2017 ◽  
Vol 2017 ◽  
pp. 1-12
Author(s):  
Hare Krishna ◽  
Neha Goel
Keyword(s):  
Maximum Likelihood ◽  
Censored Data ◽  
Geometric Distribution ◽  
Information Matrix ◽  
Bayes Estimation ◽  
Data Set ◽  
Monte Carlo Simulation Study ◽  
Randomly Censored Data ◽  
Highest Posterior Density ◽  
Randomly Censored

In this article, we study the geometric distribution under randomly censored data. Maximum likelihood estimators and confidence intervals based on Fisher information matrix are derived for the unknown parameters with randomly censored data. Bayes estimators are also developed using beta priors under generalized entropy and LINEX loss functions. Also, Bayesian credible and highest posterior density (HPD) credible intervals are obtained for the parameters. Expected time on test and reliability characteristics are also analyzed in this article. To compare various estimates developed in the article, a Monte Carlo simulation study is carried out. Finally, for illustration purpose, a randomly censored real data set is discussed.

A Cramer-von Mises Statistic for Randomly Censored Data

Biometrika ◽  
1976 ◽  
Vol 63 (3) ◽  
pp. 465 ◽  
Author(s):  
James A. Koziol ◽  
Sylvan B. Green
Keyword(s):  
Censored Data ◽  
Von Mises Statistic ◽  
Von Mises ◽  
Randomly Censored Data ◽  
Randomly Censored ◽  
Cramer Von Mises
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