Question

I have a setup that looks like below

for(V in (seq(1, 250, by = 5))){
   for(n in (seq(1, 250, by = 5))){

        # 1) Working Algorithm creating a probability 
             ie. vector in range [0:1] 

        # 2) Take the natural log of this probability 
        a <-  log(lag(Probability), base = exp(1))

        # 3) calculate price differences
        b <-  abs(diff(Price) -1)

        # 4) Then compute correlation between a and b
        cor(a, b) 

        # 5) Here I'd like to save this in the corresponding index of matrix
   }
}

So that I get a [V, n] sized matrix as output, that collects from each loop.

I have a few problems with this.

• The first problem is that my correlation is not computable, as the Probability is often 0, creating a ln(0) = -Inf input in the ln(Probability) vector. Is there a way to compute the std.dev or cor of a Ln vector with -Inf inputs?

• My second question is how I save this correlation output into a matrix generated for each loop?

Thanks for your help. I hope this is clear enough.

Answer 1

For your second question (My second question is how I save this correlation output into a matrix generated for each loop?), you could initialise a matrix before the loop and store each computed correlation in the corresponding index like:

sz <- seq(1, 250, by = 5)
out_mat <- matrix(0, nrow=length(sz), ncol=length(sz))
# then continue with your for-loop
for (V in 1:length(sz)) {
    for(n in length(sz)) {
        # here instead of accessing V and n in computing probability
        # use sz[V] and sz[n]
        ...
        ...
        # after computing the correlation, here use V and n (not sz[V] or sz[n])
        out_mat[V, n] <- c # c holds the value of cor(a,b)
    }
 }