Q5. Consider a Markov chain {Xn|n ≥ 0} with state space S = {0, 1, ·...
Q5. Consider a Markov chain {Xn|n ≥ 0} with state space S = {0, 1, · · · } and transition matrix (pij ). Find (in terms QA for appropriate A) P{ max 0≤k≤n Xk ≤ m|X0 = i} .
Q6. (Flexible Manufacturing System). Consider a machine which can produce three types of parts. Let Xn denote the state of the machine in the nth time period [n, n + 1) which takes values in {0, 1, 2, 3}. Here 0 means machine is idle in the time period, i = 1, 2, 3 means the machine is producing type i part in the time period. The process {Xn|n ≥ 0} is assumed to be a Markov chain with transition matrix P = 1 5 1 5 1 5 2 5 1 9 1 3 1 9 4 9 1 5 0 2 5 2 5 1 5 1 5 1 5 0 1 2 Find the probability that the machine will be idle for the next n periods given that X0 = 1.
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Q5. Consider a Markov chain {Xn|n ≥ 0} with state space S = {0,
1, ·...
A Markov chain {Xn, n ≥ 0} with state space S = {0, 1, 2} has...
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].
Suppose that {Xn} is a Markov chain with state space S = {1, 2}, 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...
A Markov chain {Xn, n ≥ 0} with state space S = {0, 1, 2, 3,...
A Markov chain {Xn, n ≥ 0} with state space S = {0, 1, 2, 3, 4,
5} has transition probability matrix P.
ain {x. " 0) with state spare S-(0 i 2.3.45) I as transition proba- bility matrix 01-α 0 0 1/32/3-3 β/2 0 β/2 0 β/2 β/21/2 0001-γ 0 0 0 0 (a) Determine the equivalence classes of communicating states for any possible choice of the three parameters α, β and γ; (b) In all cases, determine if...
Consider the Markov chain X0,X1,X2,... on the state space S = {0,1} with transition matrix P=...
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.
6. Suppose Xn is a two-state Markov chain with transition probabilities (Xn, Xn+1), n = 0,...
6. Suppose Xn is a two-state Markov chain with transition probabilities (Xn, Xn+1), n = 0, 1, 2, Write down the state space of the Markov chain Zo, Zi, . . . and determine the transition probability matrix.
2. The Markov chain (Xn, n = 0,1, 2, ...) has state space S = {1,...
2. The Markov chain (Xn, n = 0,1, 2, ...) has state space S = {1, 2, 3, 4, 5} and transition matrix (0.2 0.8 0 0 0 0.3 0.7 0 0 0 P= 0 0.3 0.5 0.1 0.1 0.3 0 0.1 0.4 0.2 1 0 0 0 0 1 ) (a) Draw the transition diagram for this Markov chain.
Consider the process E here Xn is the outcome of a die on the nth roll at XnEN is a Markov chain. (b) Determine the state space S and the transition matrix P (with, as usual, reasoning Consider...
Consider the process E here Xn is the outcome of a die on the nth roll at XnEN is a Markov chain. (b) Determine the state space S and the transition matrix P (with, as usual, reasoning
Consider the process E here Xn is the outcome of a die on the nth roll at XnEN is a Markov chain. (b) Determine the state space S and the transition matrix P (with, as usual, reasoning
Let Xn be a Markov chain with state space {0, 1, 2}, and transition probability matrix...
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
5. Let (Xn)n be a Markov chain on a state space S with n-step transition probabilities...
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...
A Markov chain {Xn, n ≥ 0} with state space S = {0, 1, 2, 3, 4,
5} has transition probability matrix P.
ain {x. " 0) with state spare S-(0 i 2.3.45) I as transition proba- bility matrix 01-α 0 0 1/32/3-3 β/2 0 β/2 0 β/2 β/21/2 0001-γ 0 0 0 0 (a) Determine the equivalence classes of communicating states for any possible choice of the three parameters α, β and γ; (b) In all cases, determine if...
6. Suppose Xn is a two-state Markov chain with transition probabilities (Xn, Xn+1), n = 0, 1, 2, Write down the state space of the Markov chain Zo, Zi, . . . and determine the transition probability matrix.
2. The Markov chain (Xn, n = 0,1, 2, ...) has state space S = {1, 2, 3, 4, 5} and transition matrix (0.2 0.8 0 0 0 0.3 0.7 0 0 0 P= 0 0.3 0.5 0.1 0.1 0.3 0 0.1 0.4 0.2 1 0 0 0 0 1 ) (a) Draw the transition diagram for this Markov chain.
Consider the process E here Xn is the outcome of a die on the nth roll at XnEN is a Markov chain. (b) Determine the state space S and the transition matrix P (with, as usual, reasoning
Consider the process E here Xn is the outcome of a die on the nth roll at XnEN is a Markov chain. (b) Determine the state space S and the transition matrix P (with, as usual, reasoning
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}.
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