Simplicially constrained regression models for proportions in both sides. The constraint is always that the betas are non-negative and sum to 1. References: Iverson S.J.., Field C., Bowen W.D. and Blanchard W. (2004) "Quantitative Fatty Acid Signature Analysis: A New Method of Estimating Predator Diets". Ecological Monographs, 74(2): 211-235. <doi:10.1890/02-4105>.

A system that provides a streamlined way of generating
    publication ready plots for known Single-Cell transcriptomics data in
    a “publication ready” format. This is, the goal is to automatically
    generate plots with the highest quality possible, that can be used
    right away or with minimal modifications for a research article.

Functions to implement the stability controlled 
    quasi-experiment (SCQE) approach to study the effects of 
    newly adopted treatments that were not assigned at random. This package 
    contains tools to help users avoid making statistical assumptions that rely 
    on infeasible assumptions. Methods developed in Hazlett (2019) 
    <doi:10.1002/sim.8717>.

Given bincount data from single-cell copy number profiling (segmented or unsegmented), estimates ploidy, and uses the ploidy estimate to scale the data to absolute copy numbers. Uses the modular quantogram proposed by Kendall (1986) <doi:10.1002/0471667196.ess2129.pub2>, modified by weighting segments according to confidence, and quantifying confidence in the estimate using a theoretical quantogram. Includes optional fused-lasso segmentation with the algorithm in Johnson (2013) <doi:10.1080/10618600.2012.681238>, using the implementation from glmgen by Arnold, Sadhanala, and Tibshirani.

Provides tools for estimating empirical sample complexity
    bounds for supervised learning tasks. The package supports simulation-based
    estimates of generalization curves, parametric extrapolation of empirical
    sample complexity bounds, theoretical bounds based on Vapnik-Chervonenkis
    dimension, and optional monotone Gaussian process extrapolation for users who
    install the external 'cmdstanr' workflow. For more details, see Carter and
    Choi (2024) <doi:10.31219/osf.io/evrcj>.