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# DAT 520: How to Iterate Markov Processes in R

Published on October 2017 | Categories: Graphic Art | Downloads: 47 | Comments: 0
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In a Markov process, the first matrix represents the initial probability distribution. The second matrix represents the transition matrix, from previous state to the next state. Each row in either matrix adds to 1, because they are related probabilities of moving or not moving from one state to another. (A+B=1, C+D=1, E+F=1) The exponent xrepresents which cycle is being calculated. The output in R from calculating one of these will be something like: [,1] [,2] [1,] A B You may calculate these Markov chains with a command structure like this: x1

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In a Markov process, the first matrix represents the initial probability distribution. The second matrix represents the transition matrix, from previous state to the next state. Each row in either matrix adds to 1, because they are related probabilities of moving or not moving from one state to another. (A+B=1, C+D=1, E+F=1) The exponent xrepresents which cycle is being calculated. The output in R from calculating one of these will be something like: [,1] [,2] [1,] A B You may calculate these Markov chains with a command structure like this: x1

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