TeX-to-HTML/MathML Translators TtH/TtM

C source code and R wrappers for the tth/ttm TeX-to-HTML/MathML translators.

Colors for all

Color palettes for all people, including those with color vision deficiency. Popular color palette series have been organized by type and have been scored on several properties such as color-blind-friendliness and fairness (i.e. do colors stand out equally?). Own palettes can also be loaded and analysed. Besides the common palette types (categorical, sequential, and diverging) it also includes cyclic and bivariate color palettes. Furthermore, a color for missing values is assigned to each palette.

Stability Assessment of Statistical Learning Methods

Graphical and computational methods that can be used to assess the stability of results from supervised statistical learning.

Stratified and Personalised Models Based on Model-Based Trees and Forests

Model-based trees for subgroup analyses in clinical trials and model-based forests for the estimation and prediction of personalised treatment effects (personalised models). Currently partitioning of linear models, lm(), generalised linear models, glm(), and Weibull models, survreg(), is supported. Advanced plotting functionality is supported for the trees and a test for parameter heterogeneity is provided for the personalised models. For details on model-based trees for subgroup analyses see Seibold, Zeileis and Hothorn (2016) ; for details on model-based forests for estimation of individual treatment effects see Seibold, Zeileis and Hothorn (2017) .

Embedding 'exams' Exercises as Forms in 'rmarkdown' or 'quarto' Documents

Automatic generation of quizzes or individual questions as (interactive) forms within 'rmarkdown' or 'quarto' documents based on 'R/exams' exercises.

Probability Distributions as S3 Objects

Tools to create and manipulate probability distributions using S3. Generics pdf(), cdf(), quantile(), and random() provide replacements for base R's d/p/q/r style functions. Functions and arguments have been named carefully to minimize confusion for students in intro stats courses. The documentation for each distribution contains detailed mathematical notes.

Estimate Structured Additive Regression Models with 'BayesX'

An R interface to estimate structured additive regression (STAR) models with 'BayesX'.

Recursive Partitioning of Network Models

Network trees recursively partition the data with respect to covariates. Two network tree algorithms are available: model-based trees based on a multivariate normal model and nonparametric trees based on covariance structures. After partitioning, correlation-based networks (psychometric networks) can be fit on the partitioned data. For details see Jones, Mair, Simon, & Zeileis (2020) .

Partially Additive (Generalized) Linear Model Trees

This is an implementation of model-based trees with global model parameters (PALM trees). The PALM tree algorithm is an extension to the MOB algorithm (implemented in the 'partykit' package), where some parameters are fixed across all groups. Details about the method can be found in Seibold, Hothorn, Zeileis (2016) . The package offers coef(), logLik(), plot(), and predict() functions for PALM trees.

Conditional Method Agreement Trees (COAT)

Agreement of continuously scaled measurements made by two techniques, devices or methods is usually evaluated by the well-established Bland-Altman analysis or plot. Conditional method agreement trees (COAT), proposed by Karapetyan, Zeileis, Henriksen, and Hapfelmeier (2023) , embed the Bland-Altman analysis in the framework of recursive partitioning to explore heterogeneous method agreement in dependence of covariates. COAT can also be used to perform a Bland-Altman test for differences in method agreement.