Find the stationary distribution

In summary, we can determine the stationary distribution of an irreducible homogeneous Markov chain with a doubly stochastic transition matrix by solving a system of linear equations.
  • #1
lwk99v
1
0
hi here is the question and i don't know how to solve it.
a transition matrix P is called doubly stochastic if not only its rows sum up to one, but also its columns. In exact terms, P=(pij) which i,j is the elements of E is called doubly stochastic if
pij is greater or equal to 0 and the sum of pik=1 and the sum of pkj=1
for all i,j elements E.
and X=(Xn:n is elements of natural number) be an irreducible homogeneous Markov chain with a doubly stochastic transition matrix P. Assume that the state space E is finite. Determine the stationary distribution for X.

So how could i actually solve this question?please help and many thanks.
 
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  • #2
The stationary distribution for an irreducible homogeneous Markov chain with a doubly stochastic transition matrix P can be determined by solving the following system of linear equations:p11*pi1 + p12*pi2 + ... + p1n*pin = pi1 p21*pi1 + p22*pi2 + ... + p2n*pin = pi2 ...pn1*pi1 + pn2*pi2 + ... + pnn*pin = pinwhere pi1, pi2, ..., pin are the probabilities associated with each state. The solution to this system of equations will give the stationary distribution of the chain.
 

What is a stationary distribution?

A stationary distribution is a probability distribution that remains unchanged over time in a stochastic process. This means that the probabilities of all possible states of the system remain constant, even as the system evolves.

Why is finding the stationary distribution important?

Finding the stationary distribution is important because it allows us to understand the long-term behavior of a system. It can help us predict the probabilities of different outcomes and make informed decisions based on those probabilities.

How is the stationary distribution calculated?

The stationary distribution can be calculated in several ways, depending on the type of system and the available data. In general, it involves solving a set of equations or using simulation techniques to estimate the probabilities of each state in the long run.

What factors can affect the stationary distribution?

The stationary distribution can be affected by various factors, such as the initial conditions of the system, the transition probabilities between states, and external influences. Changes in any of these factors can alter the stationary distribution and its long-term behavior.

Can the stationary distribution change over time?

In most cases, the stationary distribution remains constant over time. However, if there are significant changes in the system or its environment, the stationary distribution may also change. It is important to regularly review and update the stationary distribution to ensure its accuracy.

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