A Bayesian hierarchical nonhomogeneous hidden Markov model for multisite streamflow reconstructions

A Nonhomogeneous Hidden Markov Model for Precipitation

A stochastic model for relating precipitation occurrences at multiple rain gauge stations to broad-scale atmospheric circulation patterns (the so-called \downscaling problem") is proposed. The model is an example of a nonhomogeneous hidden Markov model and generalizes existing downscaling models in the literature. The model assumes that atmospheric circulation can be classi ed into a small numb...

A Nonhomogeneous Hidden Markov Model for Precipitation Occurrence

A nonhomogeneous hidden Markov model is proposed for relating precipitation occurrences at multiple rain gauge stations to broad-scale atmospheric circulation patterns (the so-called \downscaling problem"). We model a 15 year sequence of winter data from 30 rain stations in southwestern Australia. The rst 10 years of data are used for model development and the remaining 5 years are used for mod...

The Hierarchical Hidden Markov Model : Analysis and

We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our model is motivated by the complex multiscale structure which appears in many natural sequences, particularly in language, handwriting and speech. We seek for a systematic, unsupervised approach to the modeling of such ...

A Bayesian hidden Markov model for imperfect debugging

A Bayesian hidden Markov model for software failures

The paper presents the Bayesian analysis of a new model in software reliability, aimed to detect deterioration due to potential introduction of new bugs into the software during the development phase. Since the introduction of bugs is an unobservable process, latent variables are introduced to incorporate this characteristic into the proposed hidden Markov model. The state of the latent process...