Simulation and estimation tools for 
    various types of ambit processes, including trawl processes and weighted
    trawl processes.

Data sets that accompany the book "Designing experiments and
    analyzing data: A model comparison perspective" (4th ed.) by
    Maxwell, Delaney, and Kelley (2027; ISBN 978-1-041-25384-6; Routledge).
    Contains all of the data sets in the book's chapters and end-of-chapter
    exercises. Beginning with version 2.0, the package is tailored to the 4th
    edition of the book; for the data as distributed with the 3rd edition
    (2018), install the archived version 1.0.2 from CRAN. We recommend the
    'DMAR' package as the companion for carrying out the book's analyses; these
    analyses are illustrated in the book itself using the 'MBESS' package, which
    may be used as well. The book's companion website is available at
    <https://designingexperiments.com/> and its publisher page at
    <https://www.routledge.com/Designing-Experiments-and-Analyzing-Data-A-Model-Comparison-Perspective/Maxwell-Delaney-Kelley/p/book/9781041253846>.

Generate code for use with the Optical Mark Recognition free software Auto Multiple Choice (AMC). More specifically, this package provides functions that use as input the question and answer texts, and output the LaTeX code for AMC.

Tools for analysing the geometry of configurations in high-dimensional
    spaces using the Average Membership Degree (AMD) framework and synthetic
    configuration generation. The package supports a domain-agnostic approach
    to studying the shape, dispersion, and internal structure of point clouds,
    with applications across biological and ecological datasets, including
    those derived from deep-time records. The AMD framework builds on the idea
    that strongly coupled systems may occupy a limited set of recurrent regimes
    in state space, producing high-occupancy regions separated by sparsely
    populated transitional configurations. The package focuses on detecting
    these concentration patterns and quantifying their geometric definition
    without assuming any underlying dynamical model. It provides AMD curve
    computation, cluster assignment, and sigma-equivalent estimation, together
    with S3 methods for plotting, printing, and summarising AMD and
    sigma-equivalent objects. Mendoza (2025) <https://mmendoza1967.github.io/AMDconfigurations/>.