Need help with probability question. probability of dependent events.

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The discussion centers on calculating the probabilities of landing on various levels in a finite state Markov chain, specifically when transitioning between levels -1, 0, and 1 with defined probabilities. The user seeks to understand the steady state probability distribution for this system, which can be modeled using eigenvectors. The key to solving this problem lies in recognizing the periodic nature of the Markov chain, particularly when the number of levels (n) is even or odd. The recommended approach is to study the properties of finite state Markov chains to derive the necessary probabilities.

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Mewlove
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Would like to know what method, or distribution to use when solving a problem like this:I start from level 0. There is a probability p chance to drop to level -1 and a (1-p) chance to increase to level 1.

The levels range from level -n to level n. When it reaches level -n or level n, it resets back to 0 on the same cycle.
(Also, if you are at level -1, there is (1-p) chance to go back to level 0)

How do I calculate the percentage of landing on each level (not counting the reset), assuming I continue running this infinitely? Seems like dependent events. Is there any theorem or formula I can use?

Thanks!
 
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what you're looking for here is a finite state (recurrent, time homogenous) markov chain. Depending on whether your n is even or odd, the chain may actually be periodic with period 2 but that is a minor complication-- you want to solve for the eigenvector that gives a steady state probability distribution.

the key thing to search for is 'finite state markov chain'
 

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