Given the Markov Chain (S, ro, P) where S = {$1, 82, 83}, To , and [o 3 .21 Г.3 .14 P = |1 0 .4 p² = |0 .58 .36 P3 = |.58 .252 .376 .7 .28 .44 .2 [.14 .23 .196] 0 .7 .4 28 .518 .428 .23 .1792 .1984] 252 4372 3692 p5 [.1792 .20788 .19704] .4372 33264 37218 p6 [.20788 .191688 .197808] 33264 391672 36936

A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
icon
Related questions
Question
**Markov Chain Example**

Given the Markov Chain \((S, x_0, P)\) where \(S = \{s_1, s_2, s_3\}\), \(x_0 = \begin{bmatrix} 0 \\ 0 \\ 1 \end{bmatrix}\), and

\[ P = \begin{bmatrix}
0 & .3 & .2 \\
1 & 0 & .4 \\
0 & .7 & .4 
\end{bmatrix} \]

\[P^2 = \begin{bmatrix}
.3 & .14 & .2 \\
0 & .58 & .36 \\
.7 & .28 & .44 
\end{bmatrix} \]

\[P^3 = \begin{bmatrix}
.14 & .23 & .196 \\
.58 & .252 & .376 \\
.28 & .518 & .428 
\end{bmatrix} \]

\[P^4 = \begin{bmatrix}
.23 & .1792 & .1984 \\
.252 & .4372 & .3692 \\
.518 & .3836 & .4344 
\end{bmatrix} \]

\[P^5 = \begin{bmatrix}
.1792 & .20788 & .19704 \\
.4372 & .33264 & .37218 \\
.3836 & .45948 & .4308 
\end{bmatrix} \]

\[P^6 = \begin{bmatrix}
.20788 & .191688 & .197808 \\
.33264 & .391672 & .36936 \\
.45948 & .41664 & .432832 
\end{bmatrix} \]

Compute the probability that the Markov Chain is in state \(s_1\) at time 6.

---

**Interpretation of Matrices:**

In this case, each matrix \(P^n\) represents the state transition probabilities after \(n\) steps.

For example:

- \(P^2\) indicates the state probabilities after 2 steps.
- \(P^3\) indicates the state probabilities after 3 steps.
- and so on...

As \(n\) increases, \(P^n\) gives the probabilities of being in each state after \(n\) transitions, starting
Transcribed Image Text:**Markov Chain Example** Given the Markov Chain \((S, x_0, P)\) where \(S = \{s_1, s_2, s_3\}\), \(x_0 = \begin{bmatrix} 0 \\ 0 \\ 1 \end{bmatrix}\), and \[ P = \begin{bmatrix} 0 & .3 & .2 \\ 1 & 0 & .4 \\ 0 & .7 & .4 \end{bmatrix} \] \[P^2 = \begin{bmatrix} .3 & .14 & .2 \\ 0 & .58 & .36 \\ .7 & .28 & .44 \end{bmatrix} \] \[P^3 = \begin{bmatrix} .14 & .23 & .196 \\ .58 & .252 & .376 \\ .28 & .518 & .428 \end{bmatrix} \] \[P^4 = \begin{bmatrix} .23 & .1792 & .1984 \\ .252 & .4372 & .3692 \\ .518 & .3836 & .4344 \end{bmatrix} \] \[P^5 = \begin{bmatrix} .1792 & .20788 & .19704 \\ .4372 & .33264 & .37218 \\ .3836 & .45948 & .4308 \end{bmatrix} \] \[P^6 = \begin{bmatrix} .20788 & .191688 & .197808 \\ .33264 & .391672 & .36936 \\ .45948 & .41664 & .432832 \end{bmatrix} \] Compute the probability that the Markov Chain is in state \(s_1\) at time 6. --- **Interpretation of Matrices:** In this case, each matrix \(P^n\) represents the state transition probabilities after \(n\) steps. For example: - \(P^2\) indicates the state probabilities after 2 steps. - \(P^3\) indicates the state probabilities after 3 steps. - and so on... As \(n\) increases, \(P^n\) gives the probabilities of being in each state after \(n\) transitions, starting
Expert Solution
steps

Step by step

Solved in 2 steps with 2 images

Blurred answer
Knowledge Booster
Markov Processes and Markov chain
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, probability and related others by exploring similar questions and additional content below.
Similar questions
Recommended textbooks for you
A First Course in Probability (10th Edition)
A First Course in Probability (10th Edition)
Probability
ISBN:
9780134753119
Author:
Sheldon Ross
Publisher:
PEARSON
A First Course in Probability
A First Course in Probability
Probability
ISBN:
9780321794772
Author:
Sheldon Ross
Publisher:
PEARSON