00:01
To determine whether a state in a markov chain is recurrent or transient, we will use the rule that a state is current if and only if the expected number of times the chain visits the state starting from the state itself is infinite.
00:20
So, in the case of the markov chain with the transition probability matrix, that is given by p equals p01 minus p0, p11 minus p1, and p21 minus p2.
00:50
So, we can calculate the expected number of times the chain visits each state starting from the state itself.
00:58
So, we have the formula e of ti equals 1 plus the sum of j equals 1 cubed times pij times etj.
01:20
Solving the systems of equations, we get the following values for eti, et2, and et3.
01:32
Et1 equals the fraction of 1 minus p2 times 1 minus p1 minus p2.
01:53
For et2, we get the fraction 1 minus p1 times 1 minus p1 minus p2...