1. Let Xn be a Markov chain with states S = {1, 2} and transition matrix...
Suppose that {Xn} is a Markov chain with state space S = {1, 2},
transition matrix (1/5 4/5 2/5 3/5), and initial distribution P (X0
= 1) = 3/4 and P (X0 = 2) = 1/4. Compute the following:
(a) P(X3 =1|X1 =2)
(b) P(X3 =1|X2 =1,X1 =1,X0 =2)
(c) P(X2 =2)
(d) P(X0 =1,X2 =1)
(15 points) Suppose that {Xn} is a Markov chain with state space S = 1,2), transition matrix and initial distribution P(X0-1-3/4 and P(Xo,-2-1/4. Compute...
Problem 7.4 (10 points) A Markov chain Xo, X1, X2,.. with state space S = {1,2,3,4} has the following transition graph 0.5 0.5 0.5 0.5 0.5 0.5 2 0.5 0.5 (a) Provide the transition matrix for the Markov chain (b) Determine all recurrent and all transient states (c) Determine all communication classes. Is the Markov chain irreducible? (d) Find the stationary distribution (e) Can you say something about the limiting distribution of this Markov chain?
Problem 7.4 (10 points) A...
Suppose Xn is a Markov chain on the state space S with transition probability p. Let Yn be an independent copy of the Markov chain with transition probability p, and define Zn := (Xn, Yn). a) Prove that Zn is a Markov chain on the state space S_hat := S × S with transition probability p_hat : S_hat × S_hat → [0, 1] given by p_hat((x1, y1), (x2, y2)) := p(x1, x2)p(y1, y2). b) Prove that if π is a...
Let Xn be a Markov chain with state space {0, 1, 2}, and transition probability matrix and initial distribution π = (0.2, 0.5, 0.3). Calculate P(X1 = 2) and P(X3 = 2|X0 = 0) 0.3 0.1 0.6 p0.4 0.4 0.2 0.1 0.7 0.2
Consider the Markov chain X0,X1,X2,... on the state space S = {0,1} with transition matrix P= (a) Show that the process defined by the pair Zn := (Xn−1,Xn), n ≥ 1, is a Markov chain on the state space consisting of four (pair) states: (0,0),(0,1),(1,0),(1,1). (b) Determine the transition probability matrix for the process Zn, n ≥ 1.
A Markov chain {Xn, n ≥ 0} with state space S = {0, 1, 2} has transition probability matrix 0.1 0.3 0.6 p = 0.5 0.2 0.3 0.4 0.2 0.4 If P(X0 = 0) = P(X0 = 1) = 0.4 and P(X0 = 2) = 0.2, find the distribution of X2 and evaluate P[X2 < X4].
A4. Classify the states of the Markov chain with the following transition matrix. 0 3 0 1 Find the stationary distribution of each irreducible, recurrent subchain and hence obtain the mean recurrence time of each state. (8
Consider the Markov chain with state space {0, 1,2} and transition matrix(a) Suppose Xo-0. Find the probability that X2 = 2. (b) Find the stationary distribution of the Markov chain
2. The transition probabilities for several temporally homogeneous Markov chains with states 1,.,n appear below. For each: . Sketch a small graphical diagram of the chain (label the states and draw the arrows, but you do not need to label the transition probabilities) . Determine whether there are any absorbing states, and, if so, list them. » List the communication classes for the chain . Classify the chain as irreducible or not . Classify each state as recurrent or transient....
Suppose that we have a finite
irreducible Markov chain Xn with stationary distribution π on a
state space S. (a) Consider the sequence of neighboring pairs, (X0,
X1), (X1, X2), (X2, X3), . . . . Show that this is also a Markov
chain and find the transition probabilities. (The state space will
be S ×S = {(i,j) : i,j ∈ S} and the jumps are now of the form (i,
j) → (k, l).) (b) Find the stationary distribution...