Finite mixture models and hidden Markov models (HMMs) occupy central roles in modern statistical inference and data analysis. Finite mixture models assume that data originate from a latent ...

Online (also called "recursive" or "adaptive") estimation of fixed model parameters in hidden Markov models is a topic of much interest in times series modeling. In this work, we propose an online ...

Abstract Wavelet and hidden Markov-based modeling frameworks were developed to better capture the nonstationarity and non-Gaussian characteristics of streamflow that linear models cannot.

Hidden Markov models have an extensive history in a wide variety of pattern classification applications. In these models, an unobserved finite state Markov chain generates observed symbols whose ...

“A Hidden Markov Model Combined with Climate Indices for Multi-decadal Streamflow Simulation,” Water Resources Research, 50, 7836-7846. Abstract: Hydroclimate time series often exhibit very low ...

Hidden Markov Models (HMM) One characteristic of speech problems as well as chromosome karyotyping is that the vectors can be of variable length.