Best Prediction Method for Progressive Type-II Censored Samples under New Pareto Model with Applications
This paper describes two prediction methods for predicting the non-observed (censored) units under progressive Type-II censored samples. The lifetimes under consideration are following a new two-parameter Pareto distribution. Furthermore, point and interval estimation of the unknown parameters of th...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2021/1355990 |
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| _version_ | 1832561359314747392 |
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| author | Hanan Haj Ahmad |
| author_facet | Hanan Haj Ahmad |
| author_sort | Hanan Haj Ahmad |
| collection | DOAJ |
| description | This paper describes two prediction methods for predicting the non-observed (censored) units under progressive Type-II censored samples. The lifetimes under consideration are following a new two-parameter Pareto distribution. Furthermore, point and interval estimation of the unknown parameters of the new Pareto model is obtained. Maximum likelihood and Bayesian estimation methods are considered for that purpose. Since Bayes estimators cannot be expressed explicitly, Gibbs and the Markov Chain Monte Carlo techniques are utilized for Bayesian calculation. We use the posterior predictive density of the non-observed units to construct predictive intervals. A simulation study is performed to evaluate the performance of the estimators via mean square errors and biases and to obtain the best prediction method for the censored observation under progressive Type-II censoring scheme for different sample sizes and different censoring schemes. |
| format | Article |
| id | doaj-art-6626bb778e2d493ba7ba1522a8bf7294 |
| institution | Kabale University |
| issn | 2314-4629 2314-4785 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj-art-6626bb778e2d493ba7ba1522a8bf72942025-02-03T01:25:09ZengWileyJournal of Mathematics2314-46292314-47852021-01-01202110.1155/2021/13559901355990Best Prediction Method for Progressive Type-II Censored Samples under New Pareto Model with ApplicationsHanan Haj Ahmad0Department of Basic Science, Preparatory Year Deanship, King Faisal University, Hofuf, Al-Ahsa 31982, Saudi ArabiaThis paper describes two prediction methods for predicting the non-observed (censored) units under progressive Type-II censored samples. The lifetimes under consideration are following a new two-parameter Pareto distribution. Furthermore, point and interval estimation of the unknown parameters of the new Pareto model is obtained. Maximum likelihood and Bayesian estimation methods are considered for that purpose. Since Bayes estimators cannot be expressed explicitly, Gibbs and the Markov Chain Monte Carlo techniques are utilized for Bayesian calculation. We use the posterior predictive density of the non-observed units to construct predictive intervals. A simulation study is performed to evaluate the performance of the estimators via mean square errors and biases and to obtain the best prediction method for the censored observation under progressive Type-II censoring scheme for different sample sizes and different censoring schemes.http://dx.doi.org/10.1155/2021/1355990 |
| spellingShingle | Hanan Haj Ahmad Best Prediction Method for Progressive Type-II Censored Samples under New Pareto Model with Applications Journal of Mathematics |
| title | Best Prediction Method for Progressive Type-II Censored Samples under New Pareto Model with Applications |
| title_full | Best Prediction Method for Progressive Type-II Censored Samples under New Pareto Model with Applications |
| title_fullStr | Best Prediction Method for Progressive Type-II Censored Samples under New Pareto Model with Applications |
| title_full_unstemmed | Best Prediction Method for Progressive Type-II Censored Samples under New Pareto Model with Applications |
| title_short | Best Prediction Method for Progressive Type-II Censored Samples under New Pareto Model with Applications |
| title_sort | best prediction method for progressive type ii censored samples under new pareto model with applications |
| url | http://dx.doi.org/10.1155/2021/1355990 |
| work_keys_str_mv | AT hananhajahmad bestpredictionmethodforprogressivetypeiicensoredsamplesundernewparetomodelwithapplications |