Mixture Markov regression model with application to mosquito surveillance data analysis.

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.