Scientific Data Services

“Bayesian Penalized Transformation Models for Structured Additive Regression on the Location and Scale of Arbitrary Distributions” is the title of Johannes Brachem's lecture, which is being organised by the "Zentrum für Statistik" at Bielefeld University. It will take place on Tuesday, 14 January 2025 from 12:00 to 13:00 in W9-109.

Penalized transformation models (PTMs) are a novel form of distribution-free location-scale regression. In PTMs, the shape of the response’s conditional distribution is estimated directly from the data, and structured additive predictors are placed on its location and scale. The core of the model is a monotonically increasing transformation function that relates the response distribution to a reference distribution. The transformation function is equipped with a smoothness prior that regularizes how much the estimated distribution diverges from the reference distribution. These models can be seen as a bridge between conditional transformation models and generalized additive models for location, scale and shape. Markov chain Monte Carlo inference for PTMs can be conducted with the No-U-Turn sampler and offers straightforward uncertainty quantification for the conditional distribution as well as for the covariate effects.