Steady state transition matrix

In summary, the conversation is about understanding the concept of transition matrix and its application in a country's voting system. The main questions are about finding the transition matrix, defining steady state, and showing convergence to the steady state values. The matrix is a 2x2 matrix with specific values representing voter switches. The steady state vector is found by finding the eigenvector corresponding to the eigenvalue of 1, and it remains unchanged by the transition matrix.
  • #1
Elpmek
3
0
Ok, I'm lost. I've an exam coming up so could so with a speedy reply.

This whole transition matrix stuff is not explained at all in our lecture notes. Here's an example question:

"Suppose that a country has a fixed number of voters, all of whom vote for
either party D or party R. Every year, 1/4 of D voters change to party R and 1/3 of R voters switch to party D. Let xn and yn represent the proportions of
D and R voters respectively after n years (so that xn + yn = 1).
(a) Find the transition matrix T for this process.
(b)Explain the term ”steady state”, and find the steady state in this problem.
(c)Show that xn and yn tend to the steady state values as n goes to infinite, regardless
of the values of x0 and y0."

I don't even know what the matrix is suppose to look like...
 
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  • #2
The matrix is will have: (3/4 1/3) on the top row and (1/4 2/3) on the bottom row. Do you see why? If you multiply this by the vector (D, R) you get the specified voter switches.

Usually when you are asked to find a steady-state vector one of the eigenvalues of the matrix will be 1, and you need to find the eigenvector corresponding to this eigenvalue. The reason this is called a "steady-state" vector is that the transition matrix does not change it.
 

Related to Steady state transition matrix

1. What is a steady state transition matrix?

A steady state transition matrix is a mathematical tool used to describe the long-term behavior of a system. It shows the probabilities of transitioning from one state to another over time, assuming the system is in a stable, steady state.

2. How is a steady state transition matrix calculated?

The calculation of a steady state transition matrix involves determining the transition probabilities between states and setting up a system of equations to solve for the steady state probabilities. This can be done using various methods such as Markov chains or matrix algebra.

3. What is the significance of a steady state transition matrix in a scientific context?

In science, steady state transition matrices are often used to model and analyze complex systems, such as biological or ecological systems. They can provide insights into the long-term behavior of these systems and help make predictions about their future states.

4. Can a steady state transition matrix be used for any type of system?

While steady state transition matrices are commonly used in science, they can also be applied to other systems such as economics, sociology, and engineering. However, the system must meet certain criteria, such as being in a steady state, for the matrix to accurately represent its behavior.

5. How can a steady state transition matrix be used to make predictions?

Once the steady state transition matrix is calculated, it can be used to predict the future state of a system. By multiplying the current state vector by the transition matrix, the probabilities of the system being in each state after a certain period of time can be determined.

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