Hi, everyone. Recently I have met a problem in my project and I will show it in short.

Suppose y=b_1*\max(x-\gamma,0)+b_2*\min(x-\gamma,0)+\epsilon with \epsilon \sim Normal(0,\sigma^2), and now i have dataset (x_i,y_i). I want to estimate 4 parameters b_1,b_2,\gamma and \sigma^2. How should I use maximum or minimum functions in my Stan code?

```
data {
int<lower=0> N;
vector[N] y;
vector[N] x;
}
parameters{
real<lower=0> sigma;
real a1;
real a2;
real gamma;
}
model{
for (n in 1:N)
y[n] ~ normal(a1*max(x[n]-gamma,0)+a2*min(x[n]-gamma,0),sigma);
}
```

or the last line can be changed by

```
y[n] ~ normal(a1* (x[n]-gamma+abs(T x[n]-gamma))/2
+a2* (x[n]-gamma- abs(T x[n]-gamma))/2
,sigma);
```