EM algorithm error with while loop

Question

Hello, my project needs the EM algorithm below, where are all the codes. The error is in the loop while, which is where the hope and maximization steps are. The error message is:

"Error in while (abs(Elogv[r] - Elogv[r - 1]) >= 1e-06) { : Missing value Where TRUE/FALSE needed"**.

How do I resolve this error if the loop while does not contain commands TRUE and FALSE and, if I have already checked in detail that there is no error in the commands and there is no value NAs?

Code:

n=100
u<-runif(n)
QUANTIL <- function(u){
  Q <- rep(NA, length(u))
  for (i in 1:length(u)) {
    if(u[i] <  0.2634253829){
      Q[i] <- 1*tan(pi*(0.9490353482*u[i]-0.5))+0
    }
    if(u[i]>=0.2634253829 && u[i] < 0.7365746171){
      Q[i] <-  1*qnorm(1.4428629504*u[i]-0.2214315)+0
    }
    if(u[i]>0.7365746171){
      Q[i] <- 1*tan(pi*(0.9490353482*u[i]-0.4490353))+0
    } 
  }
  return(Q)
}
x<-QUANTIL(u)
y<-c(sort(x))
i<-seq(1,n)
v<-c(i/(n+1))

t<-QUANTIL(v)
mi<-median(y)
s<-c(y[26:73])
sigma<-sqrt(sum((s-mi)^2)/(n-1))
p=0.4731492342

alpha<-(2*t^3)/(1+t^2)^2
beta<-(1-t^2)/(1+t^2)^2
eta<-(t^4-t^2)/(1+t^2)^2
lambda<-2*t/(1+t^2)^2
gama<-(-t^2)
delta<-2*t

k<-((p*0.6930665173/sigma*sqrt(2*pi))*exp((-1/2*sigma^2)*((y-mi)^2)))/(((p*0.6930665173/sigma*sqrt(2*pi))*exp((-1/2*sigma^2)*(y-mi)^2))+((((1-p)*1.0537015317/sigma*pi))*(1/(1+((y-mi)/sigma)^2))))
r<-2
Elogv<-sum(k*((-1/2)*((y-mi)/sigma)^2))-sum(k*log(sigma*sqrt(2*pi)))-sum((1-k)*log(sigma*pi))-sum((1-k)*log(1+((y-mi)/sigma)^2))+sum(k*log(p))+(n-sum(k))*log(1-p)+log(0.6930665173)*sum(k)+log(1.0537015317)*sum(1-k)
Elogv[1]<-0

while (abs(Elogv[r]-Elogv[r-1])>=0.000001) {

  w<-(2*beta-2*k*beta+k)
  q<-k*delta+2*lambda*(1-k)
  sigma<-(sum(y*w)*sum(q)-sum(w)*sum(y*q))/(-2*sum(alpha*(1-k))*sum(q)+sum(w)*sum(k*gama-1)+2*sum(w)*sum(eta*(1-k)))                                                  
  mi<-(sum(y*w)+2*sigma*sum(alpha*(1-k)))/sum(w)
  k<-((p*0.6930665173/sigma*sqrt(2*pi))*exp((-1/2*sigma^2)*((y-mi)^2)))/(((p*0.6930665173/sigma*sqrt(2*pi))*exp((-1/2*sigma^2)*(y-mi)^2))+((((1-p)*1.0537015317/sigma*pi))*(1/(1+((y-mi)/sigma)^2))))
  Elogv[r]<-sum(k*((-1/2)*((y-mi)/sigma)^2))-sum(k*log(sigma*sqrt(2*pi)))-sum((1-k)*log(sigma*pi))-sum((1-k)*log(1+((y-mi)/sigma)^2))+sum(k*log(p))+(n-sum(k))*log(1-p)+log(0.6930665173)*sum(k)+log(1.0537015317)*sum(1-k)
  r<-r+1
  

}