Alternative to for and ifelse loops - determining whether elements lie within generated confidence intervals

I am trying to rewrite my code to not contain any for loops or ifelse loops. The purpose is to extract a matrix containing 0s and 1s depending on variable mu and variable cinterval - to generate a 1 if y0 falls within its 95th CI, and 0 y0 falls within its 95th CI, and likewise for y1. This would be repeated with both y0 and y1 for a number of modules.

mu contains values for y0 and y1; cinterval contains four rows:

1. lower 95th CI limit for y0
2. upper 95th CI limit for y0
3. lower 95th CI limit for y1
4. upper 95th CI limit for y1

cinterval looks like this. It can be programmed to have any number of modules:

> cinterval
         module.1 module.2  module.3
y0 95LCI 2.434602 1.784056  1.751713
y0 95UCI 5.988160 6.519465  6.833455
y1 95LCI 3.778811 2.681708  2.805293
y1 95UCI 9.228941 9.716476 10.258412

mu looks like this:

y0 y1 
 4  8  

The code I have is:

incinterval.fn <- function(cov.xy, mu, n1, dr) {
  cinterval <- cintervaloutput.fn(cov.xy, mu, n1, dr) # Generates matrix with 95% CI values for y0 and y1 after modules
  y0 <- NULL   # Empty vector
  for (module.no in 1:ncol(cinterval)) {
    y0 <- cbind(y0, ifelse (cinterval[1, module.no] <= mu["y0"] || mu["y0"] <= cinterval[2, module.no], 1, 0))
  }            # If y0 inside CI, 1, else 0
  y1 <- NULL   # Empty vector
  for (module.no in 1:ncol(cinterval)) {
    y1 <- cbind(y1, ifelse (cinterval[3, module.no] <= mu["y1"] || mu["y1"] <= cinterval[4, module.no], 1, 0))
  }            # If y1 inside CI, 1, else 0
  incinterval <- rbind(y0, y1) # Combines vectors
  colnames(incinterval) <- paste('module', 1:length(cinterval[1,]), sep='.')
  return(incinterval)
}

The result, incinterval, looks like this:

     module.1 module.2 module.3
[1,]        1        1        1
[2,]        1        1        1

Any assistance with more efficient coding to replace for and ifelse would be greatly appreciated! I currently use 2 for and ifeelse loops.