Converting a R code into C++ for Rcpp implementation

I have this simple "for loop" written in R which I have to convert in to C++. Following is the reproducible example of R code:

# Parameters required 
a <- 1.8
b <- 1
time.dt <- 0.1
yp <- 40 
insp.int <- 7
ph <- 2000

dt <- seq(0,ph,time.dt) # Time sequence
MD.set <- c(seq(insp.int, ph, insp.int), ph) # Decision points to check and set next inspection date

# Initialization
cum.y <- rep(0,length = length(dt)) 
init.y <- 0
flag <- FALSE

# At each iteration, the following loop generates a gamma distributed random number and cum.y keeps taking cumulative sum
# The objective is to return a vector cum.y with a conditional cumulative sum of previous iteration 
# When dt[i] matches any values in MD.Set AND corresponding cum.y[i] is also >= yp it changes the flag to true (the last if)
# At the start of the loop it checks if dt[i] matches any values in MD.Set AND flag is also true. If yes, then cum.y is reset to 0. 

for (i in 2:length(dt)){
  if (dt[i] %in% MD.set && flag == TRUE){
    cum.y[i] <- 0
    init.y <- 0
    flag <- FALSE
    next
  } else {
    cum.y[i] <- init.y + rgamma(n = 1, shape = a*time.dt, scale = b)
    init.y <- cum.y[i]
    if (dt[i] %in% MD.set && cum.y[i] >= yp){
      flag <- TRUE
    }
  }
}

res <- cbind(dt, cum.y)

Having no prior experience with C++, I am running into numerous problems when trying to do so. I need to do this conversion only to be able to use it in Rcpp package in R. Because the code runs slowly in R, specially when time.dt becomes smaller and I am guessing C++ would do the job faster. Can you help with this?

UPDATE 2: This is my proposal for the conversion with the help in comments and answer. However, I am not sure what is the equivalent of next in C++. If I use continue it keeps going through the rest of the codes (and execute the ones after else. If I use break then it comes out of the loop after the condition is true.

NumericVector cumy(double a, double b, double timedt, NumericVector dt, NumericVector MDSet, double yp){
  bool flag = false;
  int n = dt.size();
  double total = 0;
  NumericVector out(n);
  unordered_set<int> sampleSet(MDSet.begin(), MDSet.end());
  
  for (int i = 0; i < n; ++i){
    if (sampleSet.find(dt[i]) != sampleSet.end() && flag == true){
      out[i] = 0;
      total = 0;
      flag = false;
      continue;
    } else {
      out[i] = total + rgamma(1, a*timedt, b)[0];
      total = out[i];
      if (sampleSet.find(dt[i]) != sampleSet.end() && out[i] >= yp){
        flag = true;
      }
    }
  }
  return out;
}