Error code Missing value where TRUE/FALSE needed in R - r

Question

I keep getting this error message when I run my code, and I'm not sure what I need to do to fix it.
My code is as follows:
gwmh<-function(target,N,x,sigmasq){
p<-add.var()
samples<-c(x,p)
for(i in 2:N){
prop<-rnorm(1,0,sqrt(sigmasq))
if(runif(1)<min(1,(target(x+abs(prop)*p))/target(x))){
x<-x+prop
samples<-rbind(samples,c(x,p))} else{
p<--p
samples<-rbind(samples,c(x,p))
}
}
samples[(1:N)] ##delete after testing
}
The error says:
Error in if (runif(1) < min(1, (target(x + abs(prop) * p))/target(x))) { :
missing value where TRUE/FALSE needed
(add.var is a function i created to generate p in {-1,1} randomly)

Answer 1

I tested my comment and feel more comfortable offering it as an answer.
Try the following
if(TRUE){print("Test")}
# prints "Test"
if(FALSE){print("Test")}
# prints nothing
if(NA){print("Test")}
# throws your error
So within this expression:
runif(1)<min(1,(target(x+abs(prop)*p))/target(x))
the result is neither TRUE or FALSE but NAand seeing as runif()should not throw any missings it has to be in the rhs of the comparison.
Assuming that target, x, and sigmasq are all values from a df and not functions there is probably a missing value there. If this is the case and also intended you have to add an exception for catching and handling these missings that might look like this:
# test being your test expression
if(
if(is.na(test) {Do Stuff for missing values}
else {original IF statement}

Answer 2

You need to add na.rm=TRUE to the min function to account for possible NA in x.
Your function will fail if x contains NA.
target <- function(x) dnorm(x, 0, 1)
add.var <- function() runif(1, -1, 1)
gwmh <- function(target,N,x,sigmasq){
p <- add.var()
samples<-c(x,p)
for(i in 2:N){
prop<-rnorm(1,0,sqrt(sigmasq))
if(runif(1) < min(1, (target(x+abs(prop)*p))/target(x), na.rm=TRUE)){ # <- Here
x<-x+prop
samples<-rbind(samples,c(x,p))} else{
p<--p
samples<-rbind(samples,c(x,p))
}
}
samples[(1:N)] ##delete after testing
}
Now try:
gwmh(target, N=2, x=c(1,2,NA,3), sigmasq=2)
# [1] 1.00 3.14