Hi
Sorry I don't seem to have explained what I'm trying to do very clearly.
The piece of code below multiplies the two matrices together a number of
times based on the value in the matmult(InitialPop,1) term in this case one
(year), this gives me the end population for the analysis.
InitialPop<-matrix(c(500,0,0,0,0,0,0))
matmult<-function(InitialPop,N){
mat3<-matrix(c(0,rnorm(1,0.6021,0.0987),0,0,0,0,0,0,0,rnorm(1,0.6021,0.0987),0,0,0,0,1.9,0,0,rnorm(1,0.6021,0.0987),0,0,0,4.8,0,0,0,rnorm(1,0.6021,0.0987),0,0,9.7,0,0,0,0,rnorm(1,0.6021,0.0987),0,18,0,0,0,0,0,rnorm(1,0.6021,0.0987),32.6,0,0,0,0,0,0),nrow=7)
for (i in 1:N){
PVAmatrix<-matrix(c(0,rnorm(1,0.6021,0.0987),0,0,0,0,0,0,0,rnorm(1,0.6021,0.0987),0,0,0,0,1.9,0,0,rnorm(1,0.6021,0.0987),0,0,0,4.8,0,0,0,rnorm(1,0.6021,0.0987),0,0,9.7,0,0,0,0,rnorm(1,0.6021,0.0987),0,18,0,0,0,0,0,rnorm(1,0.6021,0.0987),32.6,0,0,0,0,0,0),nrow=7)
mat3<-mat3%*%PVAmatrix
}
ans<-mat3 %*% InitialPop
return(ans)
}
matmult(InitialPop,1)
The problem i have is to repeat this process say 1000 times and store this
output in a format I can export easily whilst maintaining the randomness of
the result, so that every end population is different.
Any help would be brilliant
Tom
Chris Stubben wrote:
>
>
> RFish wrote:
>>
>> I new to using R and am struggling with some matrix multiplication.
>>
>
> I'm not sure what you're trying to print, but you could place this vector
> in an expression
>
> mat3<-expression(c(0,rnorm(1,0.6021,0.0987),0,0,0,0,0,0,0,rnorm(1,0.6021,0.0987),0,0,0,0,1.9,0,0,rnorm(1,0.6021,0.0987),0,0,0,4.8,0,0,0,rnorm(1,0.6021,0.0987),0,0,9.7,0,0,0,0,rnorm(1,0.6021,0.0987),0,18,0,0,0,0,0,rnorm(1,0.6021,0.0987),32.6,0,0,0,0,0,0))
>
> # and then evaluate to get a new matrix each time
> matrix(eval(mat3), nrow=7)
>
> #I think this may be easier to follow. First create a matrix of zeros,
> stick in fertilities and then add random survival probabilities each time
>
>
> mat3<-diag(0,7)
> #fertilities
> mat3[1,3:7]<-c(1.9, 4.8, 9.7, 18, 32.6)
> # random survival on sub-diagonal
> mat3[row(mat3)==col(mat3)+1]<-rnorm(6,0.6021,0.0987)
>
>
> # and if you want to project the population over 10 time steps in a loop ?
>
> n<-matrix(c(500,0,0,0,0,0,0))
>
> popsize <- matrix(numeric(7 * 10), nrow = 7)
> for (i in 1:10) {
> popsize[, i] <- n
> mat3[row(mat3)==col(mat3)+1]<-rnorm(6,0.6021,0.0987)
> n <- mat3 %*% n
> }
>
>
> [,1] [,2] [,3] [,4] [,5] [,6] [,7]
> [,8]
> [1,] 500 0.0000 0.0000 531.6256 709.89940 940.19337 1697.52862
> 3403.6610
> [2,] 0 352.5116 0.0000 0.0000 298.97874 424.71160 561.32525
> 1027.1605
> [3,] 0 0.0000 279.8029 0.0000 0.00000 231.45988 316.83352
> 424.8883
> [4,] 0 0.0000 0.0000 147.8957 0.00000 0.00000 136.36804
> 220.7370
> [5,] 0 0.0000 0.0000 0.0000 96.92715 0.00000 0.00000
> 108.6551
> [6,] 0 0.0000 0.0000 0.0000 0.00000 69.87527 0.00000
> 0.0000
> [7,] 0 0.0000 0.0000 0.0000 0.00000 0.00000 65.86229
> 0.0000
>
>
> Chris Stubben
>
>
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