where M is a finite discrete Markov transition matrix that contains a complete description of the distributional dynamics as it maps [Q.sub.t] into [Q.sub.t+[tau]].

As in a Markov transition matrix, a concentration of contour lines along the main diagonal indicates a lack of mobility across states.

where [PSI]([t.sub.k]) is Markov transition matrix and [[[PSI]([t.sub.k])].sub.ab] denotes the jump probability from model b to model a.

Perform model mixing according to the Markov transition matrix [PSI]([t.sub.k]).

the elements of a Markov transition matrix on S, if and only if [[summation].sub.c [member of] C] [w.sub.c] x [J.sub.c] (i) < [infinity], for any i [member of] S.

Let us consider a Markov chain [([X.sub.n]).sub.n[greater than or equal to]0] on N with transitions k [right arrow] (k+1), k [right arrow] (k-1) and k [right arrow] k whose the elements of the corresponding Markov transition matrix are defined by

We first investigate the temporal dynamics of poverty rates by using the

Markov Transition matrix, which allows modeling the change in poverty rates from one period to the next and also helps to identify the relative position of U.S.

The problem of identifying the conformational states from the detailed

Markov transition matrix has received recent interest [3, 4, 7, 9].

But in the case of model uncertainty, it seems reasonable to specify a diagonal structure for the

Markov transition matrix: that is, the true economy never shifts between competing models.

One interesting strand in the literature calculates a

Markov transition matrix of movement between size categories and then calculates stationary size distributions.

* 3 X (K+1)

Markov transition matrix with elements, assumed to be constant across all districts 0 [less than or equal to] [m.sub.ij] [less than or equal to] 1 and [[summation].sup.3.sub.i=1][m.sub.ij] = 1; j = 1,K + 1.

(v) M: a k x k

Markov transition matrix for the states in Q, whose entries are defined by