stan

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

Hi,

is there any plan to implement the Generalized Pareto Distribution in brms (paul-buerkner/brms#110 (comment))? I am playing around with an extreme values analysis and it looks like extremes collected as Peak Over Threshold are better represented by the GPD instead of the generalized extreme value distribution, which I am so happy to see already in `b

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?

Summary:

The functions for the categorical distribution only accept a column vector, it would be great if it could accept also row vectors.

Description:

I use the categorical distribution to go over a matrix N_obs x N_probabilities, so it's more natural for me to use row vectors than column vectors.

Current functions:

real categorical_lpmf(ints y | vector theta)
real

Vignettes to-do list:

• filtering returned parameters from $draws()
  Showcase how one can read in only selected parameters.

• variational inference (done in #210)

• optimization (done in #210)

• profiling (done in #435)

• standalone generate_quantities

• vignette on how to use different draws formats

• example with changing adapt delta and max_tr