Log-Extended Exponential–Geometric Distribution: Moments and Inference Based on Generalized Order Statistics
In this paper, we provide explicit expressions as well as recurrence relations for the single and product moments of generalized order statistics from the log-extended exponential–geometric distribution. These relations are utilized to discuss the special cases of generalized order statistics, and s...
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MDPI AG
2023-10-01
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Series: | Symmetry |
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Online Access: | https://www.mdpi.com/2073-8994/15/10/1857 |
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author | Areej M. AL-Zaydi |
author_facet | Areej M. AL-Zaydi |
author_sort | Areej M. AL-Zaydi |
collection | DOAJ |
description | In this paper, we provide explicit expressions as well as recurrence relations for the single and product moments of generalized order statistics from the log-extended exponential–geometric distribution. These relations are utilized to discuss the special cases of generalized order statistics, and some numerical computations are carried out. Further, we use these results to obtain the best linear unbiased estimators for the location and scale parameters based on progressively Type-II right censored samples. Finally, a real data application is presented. |
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id | doaj.art-26c46959903e48ad91d3b1421fedecc8 |
institution | Directory Open Access Journal |
issn | 2073-8994 |
language | English |
last_indexed | 2024-03-10T20:51:31Z |
publishDate | 2023-10-01 |
publisher | MDPI AG |
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series | Symmetry |
spelling | doaj.art-26c46959903e48ad91d3b1421fedecc82023-11-19T18:17:47ZengMDPI AGSymmetry2073-89942023-10-011510185710.3390/sym15101857Log-Extended Exponential–Geometric Distribution: Moments and Inference Based on Generalized Order StatisticsAreej M. AL-Zaydi0Department of Mathematics and Statistics, Faculty of Science, Taif University, P. O. Box 11099, Taif 21944, Saudi ArabiaIn this paper, we provide explicit expressions as well as recurrence relations for the single and product moments of generalized order statistics from the log-extended exponential–geometric distribution. These relations are utilized to discuss the special cases of generalized order statistics, and some numerical computations are carried out. Further, we use these results to obtain the best linear unbiased estimators for the location and scale parameters based on progressively Type-II right censored samples. Finally, a real data application is presented.https://www.mdpi.com/2073-8994/15/10/1857best linear unbiased estimatorsgeneralized order statisticslog-extended exponential–geometric distributionproduct momentsrecurrence relationssingle moments |
spellingShingle | Areej M. AL-Zaydi Log-Extended Exponential–Geometric Distribution: Moments and Inference Based on Generalized Order Statistics Symmetry best linear unbiased estimators generalized order statistics log-extended exponential–geometric distribution product moments recurrence relations single moments |
title | Log-Extended Exponential–Geometric Distribution: Moments and Inference Based on Generalized Order Statistics |
title_full | Log-Extended Exponential–Geometric Distribution: Moments and Inference Based on Generalized Order Statistics |
title_fullStr | Log-Extended Exponential–Geometric Distribution: Moments and Inference Based on Generalized Order Statistics |
title_full_unstemmed | Log-Extended Exponential–Geometric Distribution: Moments and Inference Based on Generalized Order Statistics |
title_short | Log-Extended Exponential–Geometric Distribution: Moments and Inference Based on Generalized Order Statistics |
title_sort | log extended exponential geometric distribution moments and inference based on generalized order statistics |
topic | best linear unbiased estimators generalized order statistics log-extended exponential–geometric distribution product moments recurrence relations single moments |
url | https://www.mdpi.com/2073-8994/15/10/1857 |
work_keys_str_mv | AT areejmalzaydi logextendedexponentialgeometricdistributionmomentsandinferencebasedongeneralizedorderstatistics |