Summary:

It'd be nice to have a builder pattern for var contexts to make them easy to construct for testing. Something that could be used like this:

MatrixXd m(3, 2); 
...
var_context vc
  = var_context::builder()
    .matrix("a", m)
    .real("f", 2.3)
    .build();

Current Version:

v2.23.0

To be more in line with the rest of the regression families I think it would be a good idea to support lognormal distribution reparameterized with mean and standard deviation on the natural scale.

Here is the reparametrization (from ProbOnto, https://sites.google.com/site/probonto/download):

$P\left(x ; \boldsymbol{\mu}{N}, \boldsymbol{\sigma}{N}\right)=\frac{1}{x \sqrt{2 \pi \log \left

Here's Stan code I put together. The rng function includes lower and upper bounds because I needed a truncated distribution but can be removed to be consistent with other rng functions.

  real loglogistic_lpdf (real y, real alpha, real beta){
    real lalpha = log(alpha);
    real numerator = log(beta) - lalpha + (beta - 1) * (log(y) - lalpha);
    return numerator - 2 * (log1p( (y

Is your feature request related to a problem? Please describe.
While sales forecasting, it is necessary that the model is given the input about the promotions, special events that are taken care of in the prophet model as the holiday effect. Does orbit support this feature?