A non-homogeneous dynamic Bayesian network with a hidden Markov model dependency structure among the temporal data points

A generalization of Profile Hidden Markov Model (PHMM) using one-by-one dependency between sequences

The Profile Hidden Markov Model (PHMM) can be poor at capturing dependency between observations because of the statistical assumptions it makes. To overcome this limitation, the dependency between residues in a multiple sequence alignment (MSA) which is the representative of a PHMM can be combined with the PHMM. Based on the fact that sequences appearing in the final MSA are written based on th...

Forecasting with non-homogeneous hidden Markov models

We present a Bayesian forecasting methodology of discrete-time finite statespace hidden Markov models with non-constant transition matrix that depends on a set of exogenous covariates. We describe an MCMC reversible jump algorithm for predictive inference, allowing for model uncertainty regarding the set of covariates that affect the transition matrix. We apply our models to interest rates and ...

Computer Science a Bayesian Approach to Temporal Data Clustering Using the Hidden Markov Model Methodology

A Simple Hidden Markov Model for Bayesian Modeling with Time Dependent Data a Simple Hidden Markov Model for Bayesian Modeling with Time Dependent Data

SUMMARY Consider a set of real valued realizations of an observable quantity collected over time. We propose a simple hidden Markow model for these realizations in which the the predicted distribution of the next future observation given the past is easily computed. The hidden or unobservable set of parameters is assumed to have a Markov structure of a special type. The model is quite exible an...

Non radial model of dynamic DEA with the parallel network structure

  In this article, Non radial method of dynamic DEA with the parallel network structure is presented and is used for calculation of relative efficiency measures when inputs and outputs do not change equally. In this model, DMU divisions under evaluation have been put together in parallel. But its dynamic structure is assumed in series. Since in real applications there are undesirable inputs an...