This is for Stochastic Processes
This is for Stochastic Processes Let Xo, Xi,... be a Markov chain whose state space is Z (the integers). Recall the Markov property: P(X, _ in l Xo-to, X1-21, , Xn l-an l)-P(Xn-in l x, i-İn 1), Vn, V...
Let X0,X1,... be a Markov chain whose state space is Z (the
integers).
Recall the Markov property: P(Xn = in | X0 = i0,X1 = i1,...,Xn−1
= in−1) = P(Xn = in | Xn−1 = in−1), ∀n, ∀it. Does the following
always hold: P(Xn ≥0|X0 ≥0,X1 ≥0,...,Xn−1 ≥0)=P(Xn ≥0|Xn−1 ≥0)
?
(Prove if “yes”, provide a counterexample if “no”)
Let Xo,Xi, be a Markov chain whose state space is Z (the integers). Recall the Markov property: P(X,-'n l Xo-io, Xi...
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 Xo, X1,... be a Markov chain with transition matrix 1(0 1 0 P 2 0 0 1 for 0< p< 1. Let g be a function defined by g(x) =亻1, if x = 1, if x = 2.3. , Let Yn = g(x,), for n 0. Show that Yo, Xi, is not a Markov chain.
Problem 3.3 (10 points) Consider a two-state continuous time Markov chain with state space 11,2) and transition function (a) Find P(X-21 Xo = 1]. (b) Find P[X5 1, X2 2 X1-1]
Problem 3.3 (10 points) Consider a two-state continuous time Markov chain with state space 11,2) and transition function (a) Find P(X-21 Xo = 1]. (b) Find P[X5 1, X2 2 X1-1]
5. Let Xo, X1,... be a Markov chain with state space S 1,2, 3} and transition matrix 0 1/2 1/2 P-1 00 1/3 1/3 1/3/ and initial distribution a-(1/2,0,1/2). Find the following: (b) P(X 3, X2 1)
5. Let (Xn)n be a Markov chain on a state space S with n-step transition probabilities PTy = P(X,= y|Xo = x). Define (n) N x Xn=r n0 and U(G,) ΣΡ. n0 Show that (a) U(x, y)ENy|Xo= x] and (b) U(a, y) P(T, < +o0|X0= x)U(y, y), where Ty = inf {n 2 0 : X y}.
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...
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
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
Let p E [0,1] with pメ, and let (Xn)n=o b l e the Markov chain on with initia [0,1] given by distribution δο and transition matrix 11: Z Z ify=x-1 p 0 otherwise. Use the strong law of large numbers to show that each state is transient. Hint: consider another Markov chain with additional structure but with the same distribution and transition matrix
Let p E [0,1] with pメ, and let (Xn)n=o b l e the Markov chain on with...