Book of Donmon Teith

As more applications are found, interest in Hidden Markov Models continues to grow. Following comments and feedback from colleagues, students and other working

Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and

Here is a work that adds much to the sum of our knowledge in a key area of science today. It is concerned with the estimation of discrete-time semi-Markov and h

Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpos