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 ...

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.

“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 ...

Pierre Ailliot, Craig Thompson, Peter Thomson, Space: Time Modelling of Precipitation by Using a Hidden Markov Model and Censored Gaussian Distributions, Journal of the Royal Statistical Society.

Hidden Markov Models and Their Applications Publication Trend The graph below shows the total number of publications each year in Hidden Markov Models and Their Applications.

T. Rolf Turner, Murray A. Cameron, Peter J. Thomson, Hidden Markov Chains in Generalized Linear Models, The Canadian Journal of Statistics / La Revue Canadienne de ...