Conditional capability

I'm trying to create a matrix of conditional probabilities from these conditional probabilities:

I rewrote the code without a loop

a # Signal Vector 
b # Price Change Vector
Signalt<- seq(0, 1, 0.05) # Produce the 5% tiles
abst <- c(seq(1, 1.02,  by = 0.0025), 2)  #Produce the 0% to 2% tiles with 0.25% increments. Added 1 to include price change of 0 in `temp` 

xbool = ((Signal >= Signalt[1] & a < Signalt[1 + 1])  *1) # 1 for True 0 for False 
temp = (PercChange + 1)  * xbool
temp2 <- temp[which(temp > 0)]
CondProb <- cut(temp2, abst, include.lowest = T)
table(CondProb)

      

        
        
        
      

    

This outputs a table with abst columns with the number of occurrences. I certainly need it to be% of the total in the row, but I would like to start the loop first and get the output of the matrix.

Loop Original - Must be largely ignored as I changed most of the encoding setting

Signal <- runif(100)
PercChange <- abs((rnorm(100)/100))
signalt <- seq(0, 1, 0.05)
abst <- seq(0, c(0.02:1), 0.0025)



CondDistMat <- matrix(0, nrow = length(signalt), ncol = length(abst))

for(j in 1:length(signalt - 1)){
    xbool = (is.na((Signal >= signalt[j] & Signal < signalt[j + 1]) ) * 1)
    ysubset =  (PercChange * xbool[j] )
    CondProb = hist(ysubset, breaks = abst, freq = TRUE)
    CondDistMat[signalt, abst] <- CondProb$density 
}

      

        
        
        
      

    

The columns will be the percentiles defined abst

, while the rows will be 5% of the tiles defined signalt

. The idea is that through a boolean vector a 1 is created, where the absolute returns PercChange

should be in columns, and then plot the probabilities for each one signalt

.

However, I am unable to produce a conclusion - can anyone spot the error (s)? thanks in advance

The desired output should look something like the attached image .