How to handle missing values in Stan

Hi,
I developed a model which works well. But now, I have data with missing values and I’m not sure how I can handle it in rstan. I got an error message that says ‘‘Stan does not support NA (in y) in data’’. Can anyone help me with handling the missing values? I attach the data and the code below.
Antigen_Decay_Nan.csv (8.0 KB)

#STAN Code
data {
int N;
int K;
real x[K];
real y[N,K];
}
parameters {
real beta;
real<lower=1> sigma;
real<lower=1> muu;
real<lower=0> sigmau;
vector[N] U_raw;
}

transformed parameters {
real nu[N,K];
vector[N] U=U_raw * sigmau+muu;
for(n in 1:N){
for(k in 1:K){
nu[n,k]=U[n]+beta * x[k];
}
}
}

model {

    U_raw ~std_normal();
    for(n in 1:N){
      for (k in 1:K){
      y[n,k] ~ normal(nu[n,k],sigma);
      }
    }

}

#R_Code

datay<- read.csv(“Antigen_Decay_Nan.csv”)
N=100
age=c(6.5, 7.5, 10.5,13.5,16.5,21.5)
n=length(age)
X<-log(age-5.5)
antigen_dat ← list(N = N,
K = n,
x = X,
y=datay)
fit ← stan(file = ‘measles_stan.stan’, data = antigen_dat)
print(fit, pars = c(“beta”, “muu”,“sigmau”, “sigma”))
traceplot(fit, pars = c(“beta”, “muu”,“sigmau”, “sigma”), inc_warmup = FALSE, nrow = 2)