Hidden Markov model for discrete circular-linear wind data time series

作者：Mastrantonio Gianluca^*; Calise Gianfranco

来源：Journal of Statistical Computation and Simulation, 2016, 86(13): 2611-2624.

DOI：10.1080/00949655.2016.1142544

• Invariant wrapped Poisson
• hurdle model
• discrete circular variable
• non-parametricBayesian
• Dirichlet process

In this work, we deal with a bivariate time series of wind speed and direction. Our observed data have peculiar features, such as informative missing values, non-reliable measures under a specific condition and interval-censored data, that we take into account in the model specification. We analyse the time series with a non-parametric Bayesian hidden Markov model, introducing a new emission distribution, suitable to model our data, based on the invariant wrapped Poisson, the Poisson and the hurdle density. The model is estimated on simulated datasets and on the real data example that motivated this work.

• 出版日期2016