On 20-02-2012, at 16:11, <murali.me...@avivainvestors.com>
<murali.me...@avivainvestors.com> wrote:
> Folks,
>
> I'm trying to get stats from a matrix for each transition from one state to
> another.
>
> I have a matrix x as below.
>
> structure(c(0, 2, 2, 2, 0, 0, 0, 1, 1, 1, 1, 2, 2, 1, 1, 1, 0,
> 0, 2, 2, 0.21, -0.57, -0.59, 0.16, -1.62, 0.18, -0.81, -0.19,
> -0.76, 0.74, -1.51, 2.79, 0.41, 1.63, -0.86, -0.81, 0.39, -1.38,
> 0.06, 0.84, 0.51, -1, -1.29, 2.15, 0.39, 0.78, 0.85, 1.18, 1.66,
> 0.9, -0.94, -1.29, -0.23, -0.92, -0.21, 1.02, -0.77, -0.68, -0.33,
> 0.04), .Dim = c(20L, 3L), .Dimnames = list(NULL, c("State", "V1",
> "V2")))
>
> Is it possible to get, say, mean values of each variable in state 1 when the
> previous state was 0, in state 2 when the previous state was 0, and so on
> with all available transitions between states 0, 1, 2?
>
> In the above case, mean of V1 in state 2 when previous state was 0 would be
>
> mean(c(-0.57, -0.59, 0.16, 0.06, 0.84)) = -0.02
>
What do you mean by previous state.
I do this
> x <- cbind(c(NA, x[,"State"][-nrow(x)]), x)
> colnames(x)[1] <- "State.prev"
> x
State.prev State V1 V2
[1,] NA 0 0.21 0.51
[2,] 0 2 -0.57 -1.00
[3,] 2 2 -0.59 -1.29
[4,] 2 2 0.16 2.15
[5,] 2 0 -1.62 0.39
[6,] 0 0 0.18 0.78
[7,] 0 0 -0.81 0.85
[8,] 0 1 -0.19 1.18
[9,] 1 1 -0.76 1.66
[10,] 1 1 0.74 0.90
[11,] 1 1 -1.51 -0.94
[12,] 1 2 2.79 -1.29
[13,] 2 2 0.41 -0.23
[14,] 2 1 1.63 -0.92
[15,] 1 1 -0.86 -0.21
[16,] 1 1 -0.81 1.02
[17,] 1 0 0.39 -0.77
[18,] 0 0 -1.38 -0.68
[19,] 0 2 0.06 -0.33
[20,] 2 2 0.84 0.04
The mean of V1 in state 2 when the previous state is 0 would be in my
interpretation
mean(c(-0.57, 0.06))
> while the mean of V1 in state 0 when previous state was 2 would be:
>
> mean(c(1.62, 0.18, -0.81)) = 0.33
>
Your second case would be the mean of -1.62
Berend
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