Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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A spatial analysis of Neyman-Scott rectangular pulses model using an approximate likelihood function

근사적 우도함수를 이용한 Neyman-Scott 구형펄스모형의 공간구조 분석

  • Lee, Jeongjin (Department of Statistics, Kyungpook National University) ;
  • Kim, Yongku (Department of Statistics, Kyungpook National University)
  • Received : 2016.07.04
  • Accepted : 2016.07.20
  • Published : 2016.09.30
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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.

Neyman-Scott 구형펄스모형 (Neyman-Scott rectangular pulses model; NSRPM)은 강우의 발생, 강우세포의 강우강도 그리고 지속시간으로 표현되는 점과정에 기초한 강우생성 모형으로, 기존의 구형펄스모형 (rectangular pulse model)과 비교해서 강우사상의 군집특성을 잘 반영하기 때문에 여러 연구에서 많이 사용되는 모형이다. 하지만 NSRPM의 매개변수를 추정하는데 있어서 모멘트를 이용한 여러가지 최적화 기법들은 그 계산이 복잡하고 또한 목적함수의 구성에 따라 추정값의 변동도 크게 나타난다. 이를 보완하기 위해서, 최근 누적강수량에 대한 근사적인 우도함수 (approximated likelihood function)와 이를 통해 NSRPM의 매개변수를 추정하는 방법이 소개되었다. 본 논문에선 이 근사적 우도함수를 바탕으로 계층적 베이지안 모형을 이용하여 NSRPM에 공간구조를 표현하고 이를 통해 강우생성 모형의 공간적 특성을 알아보고자 한다.

Keywords

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