Transforming draws from the normal distribution to their equivalent value in the truncated normal distribution

Dear all,

I’m currently working on a project where I’d like to use Stan to transform the values I’ve drawn from a particular normal distribution to the equivalent value from the truncated normal distribution. I’d like to do this in stan because I reference the value immediately below. In addition, when I use R for truncation, there’s a weird spike at the halfway point of the lower bound (5) in this case. However, I’m not sure how to do so. I’ve tried by specifying the below (alpha_jdy[n] is the vector of values I’d like to convert) but I keep running into issues where I get the below error. I’ve tried specifying the init_r as various negative value.

Chain 1: Rejecting initial value:
Chain 1:   Log probability evaluates to log(0), i.e. negative infinity.
Chain 1:   Stan can't start sampling from this initial value.
[1] "Error in sampler$call_sampler(args_list[[i]]) : Initialization failed."
This is my code. 
// The input data is the module-year mu for 
data {
  int<lower=0> N;
  vector[N] alpha_jdy;
  vector[N] mu_my;
  vector[N] sigma_mu;
  vector[N] sigma_alpha;

parameters {
  vector[N] alpha_hat_jdy;

model {
  for (n in 1:N) {
    alpha_jdy[n] ~ normal(mu_my[n], sigma_mu[n]) T[-10, 0];
    alpha_hat_jdy[n] ~ normal(alpha_jdy[n], sigma_alpha[n]);