Bayesian New Hierarchical Laplace Prior Distributions of Tobit Quantile Regression
| المصدر: | مجلة القادسية للعلوم الإدارية والاقتصادية |
|---|---|
| الناشر: | جامعة القادسية - كلية الادارة والاقتصاد |
| المؤلف الرئيسي: | Al-Husseini, Fadel Hamid Hadi (Author) |
| مؤلفين آخرين: | Jaber, Esraa Hatem Abed (Co-Author) |
| المجلد/العدد: | مج25, ع1 |
| محكمة: | نعم |
| الدولة: |
العراق |
| التاريخ الميلادي: |
2023
|
| الصفحات: | 210 - 221 |
| ISSN: |
1816-9171 |
| رقم MD: | 1367981 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | EcoLink |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Tobit Quantile Regression | Hierarchical Posteriors Distribution | A New Hierarchical Prior | MCMC Algorithm
|
| رابط المحتوى: |
الناشر لهذه المادة لم يسمح بإتاحتها. |
| المستخلص: |
In current paper, we introduced a new method linked with a new hierarchical Laplace prior distributions via scale mixture of Uniform distribution mixing with standard exponential distribution. This mixture to Laplace prior distributions provide us attractive algorithm, it have a good features to being efficiency to achieving variables selection and coefficient estimations in Tobit quantile regression model. simulation examples and real data set are employed to evaluation our method with Bayesian and non-Bayesian methods in variable selection filed . Both simulation approach and real data shown the our proposed method have best performance compared with other methods. |
|---|---|
| ISSN: |
1816-9171 |
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