Semi-Markov processes extend traditional Markov models by explicitly accounting for the time spent in each state before transitioning. This added temporal dimension is particularly valuable in credit ...
High-order Markov chain models extend the conventional framework by incorporating dependencies that span several previous states rather than solely the immediate past. This extension allows for a ...
The Annals of Statistics, Vol. 4, No. 6 (Nov., 1976), pp. 1219-1235 (17 pages) The paper deals with continuous time Markov decision processes on a fairly general state space. The rewards are ...
The amino acid sequence of the transmembrane protein and its corresponding positions on the cell membrane are transformed into a hidden Markov process. After evaluating the parameters, the Viterbi ...
Abstract Let π = {ππ}πβ₯β be a Markov chain defined on a probability space (Ξ©, β±, β) valued in a discrete topological space π that consists of a finite number of real π × π matrices. As usual, ...
This paper proposes a hidden state Markov model (HMM) that incorporates workersβ unobserved labor market attachment into the analysis of labor market dynamics. Unlike previous literature, which ...
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