gamlss

An extension of XGBoost to probabilistic modelling

An extension of LightGBM to probabilistic modelling

An extension of CatBoost to probabilistic modelling

A package for online distributional learning.

Boosting models for fitting generalized additive models for location, shape and scale (GAMLSS) to potentially high dimensional data. The current relase version can be found on CRAN (https://cran.r-project.org/package=gamboostLSS).

Interpretable additive models for tabular data: classical GAMs (with REML smoothness selection, inference, shape constraints & diagnostics) plus neural additive models (NAM, NBM, NodeGAM, GPNAM, SIAN, SPAM, and more) for regression, classification, and distributional regression.

An extension of Py-Boost to probabilistic modelling

Toolbox to estimate, automatically regularize, and select between Generalized Additive Mixed Models and their extensions in Python

RefCurv: A Software for the Construction of Pediatric Reference Curves

A general modelling framework for specifying and fitting models to empirical fundamental diagrams of road traffic, and for comparing the model fits using information criteria

A Python library for Generalized Additive Models (GAMs) with flexible smoothing, principled inference, and beautiful visualizations.

Shiny App: Calculation of Age-dependent Reference Intervals (AdRI)

Framework for the visualization of distributional regression models

Shiny App for regression analysis using GAMLSS

Shiny App: Calculation of Age-dependent Reference Intervals with GAMLSS (AdRI_GAMLSS)

This repo provides supplemental material for the article titled: "Assessing Potential Heteroscedasticity in Psychological Data: A GAMLSS approach"

Fast GAMLSS surrogate for Hall dynamic weight change model (used in microsimulation)

MSc dissertation repository implementing gradient boosting for power logit and inflated power logit regression models

LaTeX code for my master's thesis.

Generalized Additive Models for Location, Scale and Shape in PyTorch.