  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 analyze the time series with a non-parametric Bayesian hidden Markov model,
introducing a new emission distribution based on the invariant wrapped Poisson,
the Poisson and the hurdle density, suitable to model our data. The model is
estimated on simulated datasets and on the real data example that motivated
this work.
