Use of non-homogeneous Poisson process (NHPP) in presence of change-points to analyze drought periods: a case study in Brazil

被引：0
|
作者：
Jorge Alberto Achcar
Emílio Augusto Coelho-Barros
Roberto Molina de Souza
机构：
[1] Universidade de São Paulo,Departamento de Medicina Social, FMRP
[2] Universidade Tecnológica Federal do Paraná,Departamento de Matemática
来源：
Environmental and Ecological Statistics | 2016年 / 23卷
关键词：
Bayesian inference; Change-points; Non-homogeneous Poisson processes; Power law process; Rain precipitation; Standard Precipitation Index;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Rain precipitation in the last years has been very atypical in different regions of the world, possibly, due to climate changes. We analyze Standard Precipitation Index (SPI) measures (1, 3, 6 and 12-month timescales) for a large city in Brazil: Campinas located in the southeast region of Brazil, São Paulo State, ranging from January 01, 1947 to May 01, 2011. A Bayesian analysis of non-homogeneous Poisson processes in presence or not of change-points is developed using Markov Chain Monte Carlo methods in the data analysis. We consider a special class of models: the power law process. We also discuss some discrimination methods for the choice of the better model to be used for the rain precipitation data.
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页码：405 / 419
页数：14
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