liesel 0.5.1

A probabilistic programming framework with a focus on semi-parametric regression

Liesel: A Probabilistic Programming Framework

Liesel is a probabilistic programming framework with a focus on semi-parametric regression. It includes:

• Liesel, a library to express statistical models as Probabilistic Graphical Models (PGMs). Through the PGM representation, the user can build and update models in a natural way.
• Goose, a library to build custom MCMC algorithms with several parameter blocks and MCMC kernels such as the No U-Turn Sampler (NUTS), the Iteratively Weighted Least Squares (IWLS) sampler, or different Gibbs samplers. Goose also takes care of the MCMC bookkeeping and the chain post-processing.
• Liesel-GAM, a modeling library built on Liesel which assists the user with the configuration of semi-parametric regression models such as Generalized Additive Models for Location, Scale and Shape (GAMLSS) with different response distributions, spline-based smooth terms and shrinkage priors.

The name "Liesel" is an homage to the Gänseliesel fountain, landmark of Liesel's birth city Göttingen.

Resources

• Paper on arXiv
• Liesel & Goose repo
• Liesel & Goose API docs
• Liesel-GAM repo
• Tutorials