INVARIANCE OF ASTATE ESTIMATION OF A FINITE DISCRETE-TIME MARKOV CHAIN

2021 ◽  
Vol 57 (6) ◽  
pp. 76-81
Author(s):  
E. A. Perepelkin
Keyword(s):  
Markov Chain ◽  
Discrete Time ◽  
Discrete Time Markov Chain

Lumpability for non-irreducible finite markov chains

1984 ◽  
Vol 21 (03) ◽  
pp. 567-574 ◽  
Author(s):  
Atef M. Abdel-Moneim ◽  
Frederick W. Leysieffer
Keyword(s):  
Markov Chain ◽  
Markov Chains ◽  
State Space ◽  
Discrete Time ◽  
The State ◽  
Discrete Time Markov Chain ◽  
Finite Markov Chains

Conditions under which a function of a finite, discrete-time Markov chain, X(t), is again Markov are given, when X(t) is not irreducible. These conditions are given in terms of an interrelationship between two partitions of the state space of X(t), the partition induced by the minimal essential classes of X(t) and the partition with respect to which lumping is to be considered.

Time reversal and age distributions, I. Discrete-time Markov chains

1980 ◽  
Vol 17 (1) ◽  
pp. 33-46 ◽  
Author(s):  
S. Tavaré
Keyword(s):  
Population Genetics ◽  
Markov Chain ◽  
Markov Chains ◽  
Discrete Time ◽  
Time Reversal ◽  
Age Distribution ◽  
Applied Probability ◽  
Discrete Time Markov Chain

The connection between the age distribution of a discrete-time Markov chain and a certain time-reversed Markov chain is exhibited. A method for finding properties of age distributions follows simply from this approach. The results, which have application in several areas in applied probability, are illustrated by examples from population genetics.

scholarly journals Recursive smoothers for hidden discrete-time Markov chains

2005 ◽  
Vol 2005 (3) ◽  
pp. 345-351
Author(s):  
Lakhdar Aggoun
Keyword(s):  
Markov Chain ◽  
Markov Chains ◽  
Em Algorithm ◽  
Discrete Time ◽  
Expectation Maximization ◽  
Discrete Time Markov Chain ◽  
Proposed Model

We consider a discrete-time Markov chain observed through another Markov chain. The proposed model extends models discussed by Elliott et al. (1995). We propose improved recursive formulae to update smoothed estimates of processes related to the model. These recursive estimates are used to update the parameter of the model via the expectation maximization (EM) algorithm.

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