Spatial Weibull regression with multivariate log gamma process and its applications to China earthquake economic loss,Statistics and Its Interface

当前位置： X-MOL 学术 › Stat. Interface › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Spatial Weibull regression with multivariate log gamma process and its applications to China earthquake economic loss
Statistics and Its Interface ( IF 0.3 ) Pub Date : 2021-08-11 , DOI: 10.4310/21-sii672
Hou-Cheng Yang ₁ , Yishu Xue ₂ , Lijiang Geng ₂ , Guanyu Hu ₃

Affiliation

Bayesian spatial modeling of heavy-tailed distributions has become increasingly popular in various areas of science in recent decades. We propose a Weibull regression model with spatial random effects for analyzing extreme economic loss. Model estimation is facilitated by a computationally efficient Bayesian sampling algorithm utilizing the multivariate Log-Gamma distribution. Simulation studies are carried out to demonstrate better empirical performances of the proposed model than the generalized linear mixed effects model. An earthquake data obtained from Yunnan Seismological Bureau, China is analyzed. Logarithm of the Pseudo-marginal likelihood values are obtained to select the optimal model, and Value-at-risk, expected shortfall, and tail-value-at-risk based on posterior predictive distribution of the optimal model are calculated under different confidence levels.

更新日期：2021-08-12

点击分享查看原文

点击收藏

公开下载

阅读更多本刊最新论文本刊介绍/投稿指南11