Journal of Data Science ›› 2020, Vol. 18 ›› Issue (2): 376-389.doi: 10.6339/JDS.202004_18(2).0009

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Statistical Inference for K Exponential Populations Under Joint Progressive Type-I Censored Scheme

O.E. Abo-Kasem1 and Mazen Nassar1,2   

  1. 1 Department of Statistics, Faculty of Commerce, Zagazig University, Egypt.  2 Department of Statistics, Faculty of Science, King Abdulaziz University, Kingdom of Saudia Arabia.

  • Online:2020-04-15 Published:2020-05-10

Abstract: In this article, the maximum likelihood estimators of the k independent exponential populations parameters are obtained based on joint progressive type- I censored (JPC-I) scheme. The Bayes estimators are also obtained by considering three different loss functions. The approximate confidence, two Bootstrap confidence and the Bayes credible intervals for the unknown parameters are discussed. A simulated and real data sets are analyzed to illustrate the theoretical results.

Key words: Joint progressive Type-I censored scheme, Maximum likelihood estimation, Confidence bounds, Bootstrap intervals, Bayesian estimation, Squared-error loss, LINEX loss, General entropy loss.