Spatial distribution of the earthquake in Mainland China

Xuejun Jiang, Yingzi Fu, Jiancheng Jiang and Jingzhi Li

Physica A: Statistical Mechanics and its Applications, 2019, vol. 530, issue C

Abstract: We propose a geoadditive model with spatial random effects to model the earthquake distribution in Mainland China. The error is modeled an infinite mixture of Gaussian distributions with a stochastic constraint that ensures inference on the quantiles of interest. The spatial random effects are used to capture individual area effects which allow for heterogeneity among regions. We run Bayesian quantile regression for the spatial trend of the geoadditive model under a flexible Bayesian framework. The proposed method not only allows for a full span of quantile-restricted error distributions, but also separates a large-scale geographical trend from local spatial correlation. This makes the Bayesian quantile regression feasible and flexible. Our method can be generalized to other applications that involve spatial correlation along irregular contours or in discontinuous spatial domains. Our results demonstrate the usefulness and effectiveness of the proposed methodology.

Keywords: Bayesian quantile regression; Geoadditive models; Spline; Two-dimensional surface smoothing (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:530:y:2019:i:c:s0378437119305734

DOI: 10.1016/j.physa.2019.04.177

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