The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Abstract Details
Activity Number:
|
587
|
Type:
|
Contributed
|
Date/Time:
|
Wednesday, August 3, 2011 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Section on Statistics and the Environment
|
Abstract - #301398 |
Title:
|
Hidden Markov Models Incorporating Additional Dependence in Regional Rainfall Modeling
|
Author(s):
|
Nadarajah Iyer Ramesh*+
|
Companies:
|
University of Greenwich
|
Address:
|
Department of Mathematical Sciences , London, SE10 9LS, United Kingdom
|
Keywords:
|
Hidden Markov models ;
Rainfall modelling ;
Maximum likelihood ;
Regional precipitation series ;
Daily rainfall
|
Abstract:
|
Hidden Markov models can be modified in several ways to form a rich class of flexible models that are useful in many environmental applications. One of the issues that come up very often when basic hidden Markov models are used to model environmental data is about their ability to accommodate sufficient dependence between observations. We consider a class of hidden Markov models that incorporate additional dependence among observations to model daily rainfall time series. The focus of the study is on models that introduce additional dependence between the state level and the observation level of the process and also on models that incorporate dependence at observation level. Construction of the likelihood function of the models is described along with the usual second order properties of the process. Maximum likelihood method is used to estimate the parameters of the models. Application of the proposed class of models is illustrated in an analysis of regional daily rainfall time series from South East England for the winter season during 1931 to 2010.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2011 program
|
2011 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.