Lindley’s approximation in estimating two-parameters inverted weighted exponential distribution
The Inverted Weighted Exponential (IWE) distribution can be used to describe and model real-life phenomena with unimodal or decreasing failure rates. The main aim of this study is to use the Bayesian approach to estimate the two parameters of the distribution. Two loss functions are u...
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| Format: | Article |
| Language: | English |
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Penerbit UMT
2025
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| Online Access: | http://psasir.upm.edu.my/id/eprint/118972/ http://psasir.upm.edu.my/id/eprint/118972/1/118972.pdf |
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| author | Nazri, Fatin Syazwani Zulkafli, Hani Syahida |
| author_facet | Nazri, Fatin Syazwani Zulkafli, Hani Syahida |
| author_sort | Nazri, Fatin Syazwani |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The Inverted Weighted Exponential (IWE) distribution can be used to describe and model real-life phenomena with unimodal or decreasing failure rates. The main aim of this study is to use the Bayesian approach to estimate the two parameters of the distribution. Two loss functions are used, the Squared Error Loss Function (SELF) and Linear Exponential (LINEX) loss function, using Lindley’s method. The Root Mean Square Error (RMSE) is reviewed to assess the performance of the estimation method. The results of simulation studies reveal that the scale parameter benefitted from using the Bayesian approach with a SELF. This paper mainly aims to demonstrate how the Bayesian framework can be used to estimate the parameters of the IWE distribution in addition to the conventional Maximum Likelihood estimation (MLE). A detailed simulation study is conducted to compare the performance of the Bayesian estimator and the non-Bayesian estimator, i.e., MLE. The Bayesian approach uses Lindley’s approximation with SELF and LINEX functions. The empirical results demonstrate that the scale parameter of the IWE distribution benefitted from using the Bayesian approach with a SELF. The estimators also perform better with a larger sample size, n. Nevertheless, no similar work has used Bayesian estimation for the parameters of the IWE distribution. |
| first_indexed | 2025-11-15T14:42:50Z |
| format | Article |
| id | upm-118972 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:42:50Z |
| publishDate | 2025 |
| publisher | Penerbit UMT |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1189722025-08-01T09:02:17Z http://psasir.upm.edu.my/id/eprint/118972/ Lindley’s approximation in estimating two-parameters inverted weighted exponential distribution Nazri, Fatin Syazwani Zulkafli, Hani Syahida The Inverted Weighted Exponential (IWE) distribution can be used to describe and model real-life phenomena with unimodal or decreasing failure rates. The main aim of this study is to use the Bayesian approach to estimate the two parameters of the distribution. Two loss functions are used, the Squared Error Loss Function (SELF) and Linear Exponential (LINEX) loss function, using Lindley’s method. The Root Mean Square Error (RMSE) is reviewed to assess the performance of the estimation method. The results of simulation studies reveal that the scale parameter benefitted from using the Bayesian approach with a SELF. This paper mainly aims to demonstrate how the Bayesian framework can be used to estimate the parameters of the IWE distribution in addition to the conventional Maximum Likelihood estimation (MLE). A detailed simulation study is conducted to compare the performance of the Bayesian estimator and the non-Bayesian estimator, i.e., MLE. The Bayesian approach uses Lindley’s approximation with SELF and LINEX functions. The empirical results demonstrate that the scale parameter of the IWE distribution benefitted from using the Bayesian approach with a SELF. The estimators also perform better with a larger sample size, n. Nevertheless, no similar work has used Bayesian estimation for the parameters of the IWE distribution. Penerbit UMT 2025-04-30 Article PeerReviewed text en cc_by_sa http://psasir.upm.edu.my/id/eprint/118972/1/118972.pdf Nazri, Fatin Syazwani and Zulkafli, Hani Syahida (2025) Lindley’s approximation in estimating two-parameters inverted weighted exponential distribution. Universiti Malaysia Terengganu Journal of Undergraduate Research, 7 (1). pp. 39-44. ISSN 2637-1138 https://journal.umt.edu.my/index.php/umtjur/article/view/450 10.46754/umtjur.v7i1.450 |
| spellingShingle | Nazri, Fatin Syazwani Zulkafli, Hani Syahida Lindley’s approximation in estimating two-parameters inverted weighted exponential distribution |
| title | Lindley’s approximation in estimating two-parameters inverted weighted exponential distribution |
| title_full | Lindley’s approximation in estimating two-parameters inverted weighted exponential distribution |
| title_fullStr | Lindley’s approximation in estimating two-parameters inverted weighted exponential distribution |
| title_full_unstemmed | Lindley’s approximation in estimating two-parameters inverted weighted exponential distribution |
| title_short | Lindley’s approximation in estimating two-parameters inverted weighted exponential distribution |
| title_sort | lindley’s approximation in estimating two-parameters inverted weighted exponential distribution |
| url | http://psasir.upm.edu.my/id/eprint/118972/ http://psasir.upm.edu.my/id/eprint/118972/ http://psasir.upm.edu.my/id/eprint/118972/ http://psasir.upm.edu.my/id/eprint/118972/1/118972.pdf |