A semiparametric approach to hidden Markov models under longitudinal observations

  title={A semiparametric approach to hidden Markov models under longitudinal observations},
  author={Antonello Maruotti and Tobias Ryd{\'e}n},
  journal={Statistics and Computing},
We propose a hidden Markov model for longitudinal count data where sources of unobserved heterogeneity arise, making data overdispersed. The observed process, conditionally on the hidden states, is assumed to follow an inhomogeneous Poisson kernel, where the unobserved heterogeneity is modeled in a generalized linear model (GLM) framework by adding individual-specific random effects in the link function. Due to the complexity of the likelihood within the GLM framework, model parameters may be… CONTINUE READING


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