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## 1.4 Robust Noise Models

The standard approach to linear regression is to model the noise term $$\epsilon$$ as having a normal distribution. From Stan’s perspective, there is nothing special about normally distributed noise. For instance, robust regression can be accommodated by giving the noise term a Student-$$t$$ distribution. To code this in Stan, the sampling distribution is changed to the following.

data {
...
real<lower=0> nu;
}
...
model {
y ~ student_t(nu, alpha + beta * x, sigma);
}

The degrees of freedom constant nu is specified as data.