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 loglinear 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

Description

@JamesYang007 reports in their own repo readme) that there is an issue with math/stan/math/rev/functor/adj_jac_apply.hpp on line 513 and suggests adding a stan::math:: qualifier to the use of apply to avoid conflict with C++17.

Expected Output

Compilation in C++17 on GCC 10 without having to hand tweak the code.

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?