تقرير
Generalized double Pareto shrinkage
| العنوان: | Generalized double Pareto shrinkage |
|---|---|
| المؤلفون: | Armagan, Artin, Dunson, David, Lee, Jaeyong |
| المصدر: | Statistica Sinica 23 (2013), 119-143 |
| سنة النشر: | 2011 |
| المجموعة: | Mathematics Statistics |
| مصطلحات موضوعية: | Statistics - Methodology, Mathematics - Statistics Theory, Statistics - Machine Learning |
| الوصف: | We propose a generalized double Pareto prior for Bayesian shrinkage estimation and inferences in linear models. The prior can be obtained via a scale mixture of Laplace or normal distributions, forming a bridge between the Laplace and Normal-Jeffreys' priors. While it has a spike at zero like the Laplace density, it also has a Student's $t$-like tail behavior. Bayesian computation is straightforward via a simple Gibbs sampling algorithm. We investigate the properties of the maximum a posteriori estimator, as sparse estimation plays an important role in many problems, reveal connections with some well-established regularization procedures, and show some asymptotic results. The performance of the prior is tested through simulations and an application. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1104.0861 |
| رقم الأكسشن: | edsarx.1104.0861 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |