2. Consider the Markov chain X = (Xn)neN with state space I = {A, B, C, D, E, F, G, H} and one step transition probabilities given in the following diagram: B TH HIN TH 3 4 E 11 13 1 2137 (a) Decompose the state space into its communicating classes and state the period of each class. Hence, identify the set of transient states T and a communicating class of recurrent states R. (b) Write down the one-step transition matrix P for the discrete parameter Markov chain Y with state space R, that is, the restriction of the Markov chain X to the recurrent class RCI. (c) What conditions does an invariant probability mass function for a discrete time Markov chain satisfy? Find π for the Markov chain Y.
2. Consider the Markov chain X = (Xn)neN with state space I = {A, B, C, D, E, F, G, H} and one step transition probabilities given in the following diagram: B TH HIN TH 3 4 E 11 13 1 2137 (a) Decompose the state space into its communicating classes and state the period of each class. Hence, identify the set of transient states T and a communicating class of recurrent states R. (b) Write down the one-step transition matrix P for the discrete parameter Markov chain Y with state space R, that is, the restriction of the Markov chain X to the recurrent class RCI. (c) What conditions does an invariant probability mass function for a discrete time Markov chain satisfy? Find π for the Markov chain Y.
Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter3: Matrices
Section3.7: Applications
Problem 18EQ
Related questions
Question
![2. Consider the Markov chain X = (Xn)neN with state space I = = {A, B, C, D, E, F, G, H} and
one step transition probabilities given in the following diagram:
1
534
(0)
A
71
WIN
(a) Decompose the state space into its communicating classes and state the period of
each class. Hence, identify the set of transient states T and a communicating class of
recurrent states R.
(b) Write down the one-step transition matrix P for the discrete parameter Markov chain
Y with state space R, that is, the restriction of the Markov chain X to the recurrent
class RCI.
(c) What conditions does an invariant probability mass function for a discrete time
Markov chain satisfy? Find for the Markov chain Y.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fa574767a-1b28-48ab-9fd0-f3b0aa8802f7%2Fba38eb23-7b5f-4759-aba5-3fc40af592b3%2F644tp8b_processed.png&w=3840&q=75)
Transcribed Image Text:2. Consider the Markov chain X = (Xn)neN with state space I = = {A, B, C, D, E, F, G, H} and
one step transition probabilities given in the following diagram:
1
534
(0)
A
71
WIN
(a) Decompose the state space into its communicating classes and state the period of
each class. Hence, identify the set of transient states T and a communicating class of
recurrent states R.
(b) Write down the one-step transition matrix P for the discrete parameter Markov chain
Y with state space R, that is, the restriction of the Markov chain X to the recurrent
class RCI.
(c) What conditions does an invariant probability mass function for a discrete time
Markov chain satisfy? Find for the Markov chain Y.
![(d) Stating any general results that you appeal to, deduce the following:
i. Y is positive recurrent,
ii. the distribution of Y after it has been running for a very long time,
iii. the long-term proportion of time spent in each of the states,
iv. the average time, ET;, for Y to first return to each state i,
v. the long-term average value of f(X₂), where ƒ : I → R is a function with f(A)
ƒ(B) = 2, ƒ(C) = 3, ƒ (D) = 4, ƒ (E) = 5, ƒ (F) = ƒ(G) = f(H) = 6,
= 1.
vi. starting initially in state B, what is the average number of visits made to state C
before first returning to B.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fa574767a-1b28-48ab-9fd0-f3b0aa8802f7%2Fba38eb23-7b5f-4759-aba5-3fc40af592b3%2Fvkvmwv_processed.png&w=3840&q=75)
Transcribed Image Text:(d) Stating any general results that you appeal to, deduce the following:
i. Y is positive recurrent,
ii. the distribution of Y after it has been running for a very long time,
iii. the long-term proportion of time spent in each of the states,
iv. the average time, ET;, for Y to first return to each state i,
v. the long-term average value of f(X₂), where ƒ : I → R is a function with f(A)
ƒ(B) = 2, ƒ(C) = 3, ƒ (D) = 4, ƒ (E) = 5, ƒ (F) = ƒ(G) = f(H) = 6,
= 1.
vi. starting initially in state B, what is the average number of visits made to state C
before first returning to B.
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