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”)
The answer is yes
let us observe
The sum is possible since the events are disjoint for fixed k and different i that is why the events are also disjoint for different combinations of
Hence the result
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...
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, Vil. Does the following always hold: (lProve 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, _ in l Xo-to, X1-21, , Xn l-an l)-P(Xn-in...
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...
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...
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.
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}.
A Markov chain X0, X1, X2,... has transition matrix 012 0 0.3 0.2 0.5 P = 1 0.5 0.1 0.4 .2 0.3 0.3 0.4 (i) Determine the conditional probabilities P(X1 = 1,X2 = 0|X0 = 0),P(X3 = 2|X1 = 0). (ii) Suppose the initial distribution is P(X0 = 1) = P(X0 = 2) = 1/2. Determine the probabilities P(X0 = 1, X1 = 1, X2 = 2) and P(X3 = 0). 2. A Markov chain Xo, Xi, X2,. has...
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
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].
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.
1. Let {Xn, n 2 0 be a Markov Chain with state space S. Show that for any n, m-1 and JAn+m, . . . , İn+1,in-1 , . . . , io є S.