Q. Let us consider that, {X,} is a Markov chain with 5 states 0, 1, 2, 3 and 4. Suppose, Po4 =1 and when the state is in the state i, i > Othe next isequally likely to be in any of the states 0, 1, 2, .., i - 1a. What is the nature of the states of this Markov chain.b. Find whether there exists a limiting distribution of this this Markov chain and compute that if it exists.

Given that Xn is a Markov chain with 5 states 0, 1, 2, 3 and 4.

Answered: Q. Let us consider that, {X,} is a…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Determine the probability transition matrix ∥Pij∥ for the following Markov chains. Pleaseprovide the solutions step by step and provide a short explanation for each step. Let the discrete random variables ξ1, ξ2, . . . be independent and with thecommon probability mass function
Please answer #21 and explain your reasoning!
9. |Show that if X,, X2,... is a Markov chain, then it is statistically determined by its |second-order probability masses: P{X, = Xị , X, = x}, for any i, j = 1, 2,..
Suppose you have 52 cards with the letters A, B, C, ..., Z and a, b, c, ..., z written on them. Consider the following Markov chain on the set S of all permutations of the 52 cards. Start with any fixed arrangement of the cards and at each step, choose a letter at random and interchange the cards with the corresponding capital and small letters. For example if the letter "M/m" is chosen, then the cards "M" and "m" are interchanged. This process is repeated again and again. (a) Markov chain. Count, with justification, the number of communicating classes of this (b) Give a stationary distribution for the chain. (c) Is the stationary distribution unique? Justify your answer. (d) initial state. Find the expected number of steps for the Markov chain to return to its
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Please do the following question with handwritten working out
40. A Markov Chain with 4 states is currently equally likely to be in states 3 and 2, but is 4 times as likely to be in state 1 as in 3, and is 2 times as likely to be in 4 as in 1. What is the state vector that describes this situation?
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Consider the Markov chain with three states,S={1,2,3}, that has the following transition matrix 1.Draw the state transition diagram for this chain. (10 marks)
Q3) The state transition matrix of a Markov random process is given by 1/3 1/3 1/6 1/6 5/9 0 0 4/9 2/5 1/5 1/5 1/5 0 0 3/20 17/20 [ ] Draw the state transition diagram and denote all the state transition probabilities on the same. Find P[X1 = 2] List the pairs of communicating states. Find P[X2 = 3| X1 = 2] Compute P[X2 = 2 | X0 = 1] Compute P[X3 = 3, X2 = 1, X1 = 2 | X0 = 3] (vii) Find P[X4 = 4, X3 = 3, X2 = 3, X1 = 1, X0 =2] where Xt denotes the state of the random process at time instant t. The initial probability distribution is given by X0 = [2/5 1/5 1/5 1/5].
1. Prove that Weiner Process is Markovian (Markov Process).
2. Let Zbe a Markov chain on a state space S = {1,… … , m} with transition probability matrix P(i, j) = Tij. Suppose that sample paths of Z are observed from which we record Njj #i →→ j transitions of Z, m N₁ = [N₁; (# transitions out of state i). j=1 It is known that the likelihood function of the observations of Z is given by m Nij ΠΠΠ. i=1_ j=1 L = Incorporating the constraint j = 1 for each i = S, j=1 m (a) Write the loglikelihood function of the observation. (b) Show that the maximum likelihood estimator of i → j transition probability ij is N = Tij = (c) Let m = 2 and assume that the number of transitions of Z is given by the matrix Nij N₁ 50 100 25 75 Use the above information to derive estimators for 11, 12, 721 and 22.

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