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http://dx.doi.org/10.7465/jkdi.2016.27.5.1119

A spatial analysis of Neyman-Scott rectangular pulses model using an approximate likelihood function  

Lee, Jeongjin (Department of Statistics, Kyungpook National University)
Kim, Yongku (Department of Statistics, Kyungpook National University)
Publication Information
Journal of the Korean Data and Information Science Society / v.27, no.5, 2016 , pp. 1119-1131 More about this Journal
Abstract
The Neyman-Scott Rectangular Pulses Model (NSRPM) is mainly used to construct hourly rainfall series. This model uses a modest number of parameters to represent the rainfall processes and underlying physical phenomena, such as the arrival of storms or rain cells. In NSRPM, the method of moments has often been used because it is difficult to know the distribution of rainfall intensity. Recently, approximated likelihood function for NSRPM has been introduced. In this paper, we propose a hierarchical model for applying a spatial structure to the NSRPM parameters using the approximated likelihood function. The proposed method is applied to summer hourly precipitation data observed at 59 weather stations (Korea Meteorological Administration) from 1973 to 2011.
Keywords
Approximated likelihood; hierarchical Bayesian modeling; Neyman-Scott rectangular pulse model; spatial analysis;
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