'ggplot' Visualizations for the 'partykit' Package

Extends 'ggplot2' functionality to the 'partykit' package. 'ggparty' provides the necessary tools to create clearly structured and highly customizable visualizations for tree-objects of the class 'party'.

Spatial and Spatiotemporal SPDE-Based GLMMs with 'TMB'

Implements spatial and spatiotemporal GLMMs (Generalized Linear Mixed Effect Models) using 'TMB', 'fmesher', and the SPDE (Stochastic Partial Differential Equation) Gaussian Markov random field approximation to Gaussian random fields. One common application is for spatially explicit species distribution models (SDMs). See Anderson et al. (2025) .

Suite of Deterministic and Robust Algorithms for Linear Regression

DetLTS, DetMM (and DetS) Algorithms for Deterministic, Robust Linear Regression.

Animated Interactive Grammar of Graphics

Functions are provided for defining animated, interactive data visualizations in R code, and rendering on a web page. The 2018 Journal of Computational and Graphical Statistics paper, describes the concepts implemented.

R Package Installation from Remote Repositories, Including 'GitHub'

Download and install R packages stored in 'GitHub', 'GitLab', 'Bitbucket', 'Bioconductor', or plain 'subversion' or 'git' repositories. This package provides the 'install_*' functions in 'devtools'. Indeed most of the code was copied over from 'devtools'.

Multinomial Logit Models for Categorical Responses and Discrete Choices

Provides estimators for multinomial logit models in their conditional logit (for discrete choices) and baseline logit variants (for categorical responses), optionally with overdispersion or random effects. Random effects models are estimated using the PQL technique (based on a Laplace approximation) or the MQL technique (based on a Solomon-Cox approximation). Estimates should be treated with caution if the group sizes are small.

Tools for Developing R Packages Interfacing with 'Stan'

Provides various tools for developers of R packages interfacing with 'Stan' < https://mc-stan.org>, including functions to set up the required package structure, S3 generics and default methods to unify function naming across 'Stan'-based R packages, and vignettes with recommendations for developers.

Access the Bioconductor Project Package Repository

A convenient tool to install and update Bioconductor packages.

Bayesian Additive Regression Trees with Stan-Sampled Parametric Extensions

Fits semiparametric linear and multilevel models with non-parametric additive Bayesian additive regression tree (BART; Chipman, George, and McCulloch (2010) ) components and Stan (Stan Development Team (2021) < https://mc-stan.org/>) sampled parametric ones. Multilevel models can be expressed using 'lme4' syntax (Bates, Maechler, Bolker, and Walker (2015) ).

Define and Work with Parameter Spaces for Complex Algorithms

Define parameter spaces, constraints and dependencies for arbitrary algorithms, to program on such spaces. Also includes statistical designs and random samplers. Objects are implemented as 'R6' classes.