Mixture Markov regression model with application to mosquito surveillance data analysis
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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
Xin Gao1, Yurong R Cao1, Nicholas Ogden2
1Department of Mathematics and Statistics, York University, Canada.
Abstract:
A mixture Markov regression model is proposed to analyze heterogeneous time series data. Mixture quasi-likelihood is formulated to model time series with mixture components and exogenous variables. The parameters are estimated by quasi-likelihood estimating equations. A modified EM algorithm is developed for the mixture time series model. The model and proposed algorithm are tested on simulated data and applied to mosquito surveillance data in Peel Region, Canada.
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