CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Estimation and Prediction for Pareto Distribution under Type-II Progressive Hybrid Censoring Scheme

by M. M. Mohie El-Din, A. Sadek, Marwa M. Mohie El-Din, M. Nagy
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 155 - Number 10
Year of Publication: 2016
Authors: M. M. Mohie El-Din, A. Sadek, Marwa M. Mohie El-Din, M. Nagy
10.5120/ijca2016912438

M. M. Mohie El-Din, A. Sadek, Marwa M. Mohie El-Din, M. Nagy . Estimation and Prediction for Pareto Distribution under Type-II Progressive Hybrid Censoring Scheme. International Journal of Computer Applications. 155, 10 ( Dec 2016), 9-15. DOI=10.5120/ijca2016912438

@article{ 10.5120/ijca2016912438,
author = { M. M. Mohie El-Din, A. Sadek, Marwa M. Mohie El-Din, M. Nagy },
title = { Estimation and Prediction for Pareto Distribution under Type-II Progressive Hybrid Censoring Scheme },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 155 },
number = { 10 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 9-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume155/number10/26639-2016912438/ },
doi = { 10.5120/ijca2016912438 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:00:53.228861+05:30
%A M. M. Mohie El-Din
%A A. Sadek
%A Marwa M. Mohie El-Din
%A M. Nagy
%T Estimation and Prediction for Pareto Distribution under Type-II Progressive Hybrid Censoring Scheme
%J International Journal of Computer Applications
%@ 0975-8887
%V 155
%N 10
%P 9-15
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, the maximum likelihood and Bayesian estimation are developed based on Type-II progressive hybrid censoring scheme from the Pareto distribution. One and two-sample Bayesian prediction is also discussed using Type-II progressive hybrid censoring scheme. Finally, numerical example is presented for illustrating all the inferential procedures developed here.

References
  1. Aggarwala, R., & Balakrishnan, N. (1998). Some properties of progressive censored order statistics from arbitrary and uniform distributions with applications to inference and simulation. Journal of statistical planning and inference, 70(1), 35-49.
  2. Raqab, M. Z., Asgharzadeh, A., & Valiollahi, R. (2010). Prediction for Pareto distribution based on progressively Type-II censored samples. Computational Statistics & Data Analysis, 54(7), 1732-1743.
  3. Balakrishnan, N., & Cohen, A. C. (2014). Order statistics & inference: estimation methods. Elsevier
  4. Childs, A., Chandrasekar, B., Balakrishnan, N., & Kundu, D. (2003). Exact likelihood inference based on Type-I and Type-II hybrid censored samples from the exponential distribution. Annals of the Institute of Statistical Mathematics, 55(2), 319-330.
  5. Pareto, V., (1897). Cours d'Economie Politique. Rouge et Cie, Paris.
  6. Davis, H. T., & Feldstein, M. L. (1979). The generalized Pareto law as a model for progressively censored survival data. Biometrika, 66(2), 299-306.
  7. Cohen, A. C., & Whitten, B. J. (1988). Parameter estimation in reliability and life span models. M. Dekker.
  8. Grimshaw, S. D. (1993). Computing maximum likelihood estimates for the generalized Pareto distribution. Technometrics, 35(2), 185-191
  9. Lwin, T. (1972). Estimation of the tail of the Paretian law. Scandinavian Actuarial Journal, 1972(2), 170-178
  10. Arnold, B. C., & Press, S. J. (1989). Bayesian estimation and prediction for Pareto data. Journal of the American Statistical Association, 84(408), 1079-1084.
  11. Basak, I., Basak, P., & Balakrishnan, N. (2006). On some predictors of times to failure of censored items in progressively censored samples. Computational statistics & data analysis, 50(5), 1313-1337.
  12. Balakrishnan, N., Childs, A., & Chandrasekar, B. (2002). An efficient computational method for moments of order statistics under progressive censoring. Statistics & probability letters, 60(4), 359-365.
  13. Balakrishnan, N., & Aggarwala, R. (2000). Progressive censoring: theory, methods, and applications. Springer Science & Business Media.
Index Terms

Computer Science
Information Sciences

Keywords

Bayesian estimation Bayesian prediction Pareto distribution Maximum likelihood estimation Type-II progressive hybrid censoring sample

Powered by PhDFocusTM