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!