. For a discrete time Markov chain with transition matrix P (py), explain what is meant...
Xn is a discrete-time Markov chain with state-space {1,2,3}, transition matrix, P = .2 .1 .7 .3 .3 .4 .6 .3 .1 and initial probability vector a = [.2,.7,.1]. The P(X2=2) =
Let Xn be a discrete Markov chain with transition matrix P .
Show that the
m-step transition probabilities are independent of the past.
Hint: it is clear for m=1, apply mathematical induction on m
2. (10 points) Consider a continuous-time Markov chain with the transition rate matrix -4 2 2 Q 34 1 5 0 -5 (a) What is the expected amount of time spent in each state? (b) What is the transition probability matrix of the embedded discrete-time Markov chain? (c) Is this continuous-time Markov chain irreducible? (d) Compute the stationary distribution for the continuous-time Markov chain and the em- bedded discrete-time Markov chain and compare the two
2. (10 points) Consider a...
1. Let (т, P) be a time-homogeneous discrete-time Markov chain with state space {1, . . . , (a) Show that the Markov chain is not stationary (i.e., SSS). (b) Suppose P is doubly stochastic and π- JJ, . . . , Đ. Then show that the Markov chain is stationary
Markov Chains Consider the Markov chain with transition matrix P = [ 0 1 1 0]. 1) Compute several powers of P by hand. What do you notice? 2) Argue that a Markov chain with P as its transition matrix cannot stabilize unless both initial probabilities are 1/2.
Please give the detail
solution to the problems.
Let (T,P) be a time-homogeneous discrete-time Markov chain with state space {1, . . . ,J) (a) Show that the Markov chain is not stationary (i.e., SSS) (b) Suppose P is doubly stochastic and π = (1,7, . 1 . Then show that the Markov chain is stationary
Let P be the n*n transition matrix of a Markov chain with a finite state space S = {1, 2, ..., n}. Show that 7 is the stationary distribution of the Markov chain, i.e., P = , 2hTi = 1 if and only if (I – P+117) = 17 where I is the n*n identity matrix and 17 = [11...1) is a 1 * n row vector with all components being 1.
Exercise 5.10. Let P be the transition matrix of a Markov chain (Xt)120 on a finite state space Ω. Show that the following statements are equivalent: (i) P is irreducible and aperiodic (ii) There exists an integer r 0 such that for all i,je Ω, (88) (ii) There exists an integer r 20 such that every entry of Pr is positive.
Consider a Markov chain with state space S = {1,2,3,4} and transition matrix P = where (a) Draw a directed graph that represents the transition matrix for this Markov chain. (b) Compute the following probabilities: P(starting from state 1, the process reaches state 3 in exactly three-time steps); P(starting from state 1, the process reaches state 3 in exactly four-time steps); P(starting from state 1, the process reaches states higher than state 1 in exactly two-time steps). (c) If the...
A Markov chain has the transition matrix P = 1.4.61 L.7 .3 Suppose that on the initial observation, the chain is in state 1 with probability 2. What is the probability that the system will be in state 1 on the next observation? 0.38 0.60 0.64 0.36 0.56