主  題：Statistical Analysis of a Generalized Hidden Markov Model

內(nèi)容簡介：This research considers a generalized hidden Markov model to investigate the dynamic patterns and possible heterogeneity of the associations and interrelationships among variables of interest in multivariate longitudinal data analysis. The model consists of a conditional latent variable model and a mixed hidden transition model to simultaneously address different types of dependencies within the data. The maximum likelihood procedure, coupled with the expectation-maximization algorithm and efficient sampling schemes, is developed to conduct parameter estimation. The issues of model selection and hypothesis testing are also addressed. The empirical performance of the proposed methodology is examined via simulation studies. A real data example is reported for illustration.

報告人：Xinyuan Song    教授   博導(dǎo)

時  間：2016-05-23    16:00

地  點(diǎn)：中和樓401

舉辦單位：經(jīng)濟(jì)與金融研究院