Gao X.,York University |
Cao Y.R.,York University |
Ogden N.,National Microbiology Laboratory Public Health Agency of Canada Canada |
Aubin L.,Environmental Health Public Health Services |
Zhu H.P.,York University
Biometrical Journal | Year: 2017
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. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.