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rmatrixdiagonalstatistical-sampling

Sample the maximum value on a matrix excluding value on main diagonal


I have a matrix X with its maximum value along the main diagonal. Firstly, want to sample one row i, and pick the maximum value along row i excluding the main diagonal value i.e max != X[i,i].

The code below usually produces results but often has an error: Error in if (MAX < l[k]) { : missing value where TRUE/FALSE needed

# initial values
n = 10
pop = runif(n,min =0,max =1)
D = matrix(rnorm(n*n,0,0.2),nrow=n)

str_mat = abs(D)
for (l in 1:n) {
  str_mat[l,l] = 1
}

int_mat = matrix(rbinom(n*n,1,z),n,n) ##z takes the values 0.1 - 0.9
for (j in 1:n) {
  int_mat[j,j] = 1
}

X = (int_mat*str_mat)*pop
b = c(1:n)  #creating a vector with the length being the dimensions of the matrix
a = sample(b,1)## sampling one value from the vector
if (sum(int_mat[a,])< n)
{
    ### int_mat is a binary matrix
    break
}}

l = X[a,]

## Ensuring the maximum value picked is not on the main diagonal
MAX = 0
j = 1
for (k in 1:length(l)) {
  if(k!=a) {
    if (MAX<l[k]) {
      MAX = l[k]
      j = k
    }
  }
}

Solution

  • Thanks everyone for your contribution. I figured out how to go about the problem. The is as below;

    X=(int_mat*str_mat)*pop    ## creating a matrix of interaction, competition strength and  population densities             
    
    repeat{
      IntRowsums=rowSums(int_mat)
      introwsums_greater=which(IntRowsums>2,arr.ind = T)
      if (length(introwsums_greater)>1){
        a= sample(introwsums_greater,1)
      }else{
        a=introwsums_greater
      }
      if (sum(int_mat[a,])< n){
        break
      }}
    
    q= ABX[a,]
    j_k=which(q!=q[a] & q!=0,arr.ind = T)     ## from the sampled row in str_mat check the position of all zeros
    k=sample(j_k,1)