Problem 2) Consider a Markov chain with states 0, 1, 2 and the following transition probability matrix[1/2 1/3 1/61P =| 0 1/3 2/31/2]li/2If p(Xo = 0) = 0.25 and p(Xo = 1) = 0.25, then find p(X2 = 1).%3D

Answered: Problem 2) Consider a Markov chain with…

A First Course in Probability (10th Edition)

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Chapter1: Combinatorial Analysis

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Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Answer all the following problems 1. A Markov chain Xo, X₁, X₂,... has the transition probability matrix 0 1 2 0.3 0.1 0 0.6 P-1 0.3 0.3 0.4 2 0.4 0.1 0.5 If it si known that the process starts in state Xo = 1, determine the probability Pr{Xo = 1, X₁0, X₂ = 2} if Pr{Xo = 1) = 0.5.
3. A rat is put into the following maze: 3 moves. 1 2 The rat has a probability of 1/4 of starting in any compartment and suppose that the rat chooses a passageway at random when it makes a move from one compartment to another at each time. Let Xn be the compartment occupied by the rat after n (a) Explain why {X₂} is a MC and find the transition matrix P. (b) Explain why the chain is irreducible, aperiodic and positive recurrent. (c) What is the limit of Pn? Explain. (d) Find the probability that the rat is in compartment 3 after two moves. (e) In the long run, how many times that the rat enters in compartment 4 in 100 movements?
Question 1.16.2 (Markov chains, Part IB, 1991, 307D) Three girls A, B and C are playing table tennis. In each game, two of the girls play against each other and the third girl does not play. The winner of any given game n plays again in game n + 1. The probability that girl x will beat girl y in any game that they play against each other is sx/(Sx+Sy) for x, y = {A,B,C}, x‡y, where sa, SB, SC represent the playing strengths of the three girls. In what proportion of games does each girl play, in the long run?
4. A Markov chain has transition matrix 6 1 3 4 Given the initial probabilities ø1 = 02 = ¢3 = , find Pr (X1 X2). %3D %3D 1/4
1. Consider a Markov chain X matrix = (Xn)n≥0 with state space S [0.2 0.4 0 0.4 0.3 0 0.7 0 0.5 0 0.5 0 0 0.1 0.9 0 (a) Which states are transient and which are recurrent? (b) Is this markov chain irreducible or reducible? = {1, 2, 3, 4} and transition
3. A discrete Markov model has state space equal to E {0, 1, 2}. The transition probabilities p are independent of r and recorded in the matrix P defined below. .7 .2 .1 P = .1 .6 .3 1 Assume that Lynn is in state 0 at time 0, and that i = .04. (a.) Determine the probability that Lynn is in state 0 at time 3. (b.) Determine the probability that Lynn transitions from state 1 at time 3 to state 2 at time 4.
What is the second row of the matrix A, if A is stochastic? Second row: 0.8 The steady state vector for A is If v= 0.5 [15] 26 then Av approaches as n gets large. A = [0.2 ? 0.5] ?
Consider the migration (Markov) matrix A = 0.7 0 0.2 0.1 0.4 0.2 0.2 0.6 0.6 Suppose that, initially, there are 96 residents in location 1, 82 residents in location 2, and 151 residents in location 3. Assume time is measured in years. Find the population in each location after 1 year. Find the population in each location after 2 years.
5. consider the example below, where the states are Condition State and the transition matrix is 0 1 23 2 Πο Good as new Operable-minimum deterioration Operable-major deterioration Inoperable and replaced by a good-as-new machine we found that the steady-state probabilities are 2 13' T1= = P = 78314 00 1 0 7 13' HARTNO LELBLINO 1 16 1 1 1 1 16 8 8 0 2 2 = π2 2 13' I3 = 2 13 (a) Find the expected recurrence time for state 0 (i.e., the expected length of time a machine can be used before it must be replaced) by solving a linear system for Moo, M10, 20, and μ30. (b) Find the expected recurrence time for state O directly by the formula Moo 1 πο =
Suppose qo = [1/4, 3/4] is the initial state distribution for a Markov process with the following transition matrix: %3D [1/2 1/2] M = [3/4 1/4] (a) Find q1, 92, and q3. (b) Find the vector v that qo M" approaches. (c) Find the matrix that M" approaches.
Question 3 Consider a discrete time Markov Chain (Xn} on the state space (1, 2, 3) with the transition matrix given as follows: P= 1/2 1/4 1/4 1/3 2/3 1/2 1/2 Then P( X1 = 3, X2 = 2,X3 = 1) is given by 3/16 O 1/12 4/18 14/36 OO
3. (a) A Markov process with 2 states is used to model the weather in a certain town. State 1 corresponds to a suny day. State 2 corresponds to a rainy day. The transition matrix for this Markov process is [0.7 0.4] 0.3 0.6 %3D (i) If today is rainy, what is the probability that tomorrow will be sunny? (ii) Find the steady state probability vector. (iii) In the long run, how many days a week are sunny?

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Problem 2) Consider a Markov chain with states 0, 1, 2 and the following transition probability matrix 1/2 1/3 1/61 P =|0 1/3 2/3 l1/2 1/2] If p(Xo = 0) = 0.25 and p(Xo = 1) = 0.25, then find p(X2 = 1).