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I'm just starting to learn about Markov chains, and would just like to know if this is a typo in the course literature, or if there is something that I don't understand.

The book gives an example of an Markov matrix, following:

Some winter days in Minnesota it seems like the snow will never stop. A Minnesotan's view of a winter may be described by the following transition matrix for a Markov chain where $r,$ $s,$ $c$ denotes the weather rain, snow and clear.

$ \begin{bmatrix} 0.2 & 0.6 & 0.2 \\ 0.1 & 0.8 & 0.1 \\ 0.1 & 0.6 & 0.3 \end{bmatrix} $

Here the first column is $r,$ second column, $s,$ third column $c$ and the same for the rows where first row is $r,$ second row is $s,$ third row is $c.$

where the book says that regardless what weather occurs on day $D_n$ the chance of snow is always at least $0.6$ on day $D_{n+1}$

But from my understanding the column is always the starting position, day $D_n$, so element $E_{2,3}$ is gives is $D_n=$ clear (column 3) with probability for snow (row 2) in $D_{n+1}=0.1$

Would anyone like to explain to me what I'm missing out on? Is the row the starting position?

Thanks!

uoiu
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1 Answers1

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In the transition matrix $(E_{i,j})$ the $i-$th row, $j-$th column element $E_{i,j}$ is the probability of a transition from sate $i$ to state $j$. So the book is correct. All the elements in the second column of the matrix are at least equal to $0.6$.

uoiu
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geetha290krm
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