Figure 1. Finite state machine for a Markov chain X0 → X1 → X2 → · · · → Xn where the random variables Xi’s take values from I = {S1, S2, S3}. The numbers T (i, j)’s on the arrows are the transition probabilities such that Tij = P (Xt+1 = Sj|Xt = Si). Definition 1.2. We say that (Xn)n≥0 is a Markov chain with initial distribution λ and transition matrix T if (i) X0 has distribution λ; (ii) for ...

In this paper, the ambiguity of nite state irreducible Markov chain trajectories is reminded and is obtained for two state Markov chain. I give an applicable example of this concept in President election

In this paper, we present a simplified higher-order Markov chain model for multiple categorical data sequences also called as simplified higher-order multivariate Markov chain model. The number of the parameters of the new model is only ) ) (( 2 sm s n O + which is less than ) (( 2 m ns O in the higher-order multivariate Markov chain model. Numerical experiments illustrate the benefits of our n...

in a finite stationary markov chain, transition probabilities may depend on some explanatoryvariables. a similar problem has been considered here. the corresponding posteriors are derived andinferences are done using these posteriors. finally, the procedure is illustrated with a real example.

in this paper occurrences of precipitation in iran was analyzed according to random processes by the applying of markov chain model. in order to do that occurrence and non-occurrence of rainfall of asfezari data base for the period of 1961/3/21 to 2004/12/31 was used. this data are for 7187 pixel and 15991 days. by using markov chain model first order two state dry and wet frequency matrix was ...

Among the class of discrete time Markovian processes, two models are widely used, the Markov chain and the Hidden Markov Model. A major di erence between these two models lies in the relation between successive outputs of the observed variable. In a visible Markov chain, these are directly correlated while in hidden models they are not. However, in some situations it is possible to observe both...