An implementation of the nonnegative garrote method that incorporates hierarchical relationships among variables. The core function, HiGarrote(), offers an automated approach for analyzing experiments while respecting hierarchical structures among effects. For methodological details, refer to Yu and Joseph (2025) <doi:10.1080/00224065.2025.2513508>. This work is supported by U.S. National Science Foundation grant DMS-2310637.

Based on large margin principle, this package performs feature selection methods: "IM4E"(Iterative Margin-Maximization under Max-Min Entropy Algorithm); "Immigrate"(Iterative Max-Min Entropy Margin-Maximization with Interaction Terms Algorithm); "BIM"(Boosted version of IMMIGRATE algorithm); "Simba"(Iterative Search Margin Based Algorithm); "LFE"(Local Feature Extraction Algorithm). This package also performs prediction for the above feature selection methods.

This package provides a graphical user interface to apply an advanced method optimization algorithm to various sampling and analysis instruments. This includes generating experimental designs, uploading and viewing data, and performing various analyses to determine the optimal method. Details of the techniques used in this package are published in Gamble, Granger, & Mannion (2024) <doi:10.1021/acs.analchem.3c05763>.

Multi-Dimensional Analysis (MDA) is an adaptation of factor analysis developed by Douglas Biber (1992) <doi:10.1007/BF00136979>. Its most common use is to describe language as it varies by genre, register, and use. This package contains functions for carrying out the calculations needed to describe and plot MDA results: dimension scores, dimension means, and factor loadings.

Implementation of the Monothetic Clustering algorithm (Chavent, 1998 <doi:10.1016/S0167-8655(98)00087-7>) on continuous data sets. A lot of extensions are included in the package, including applying Monothetic clustering on data sets with circular variables, visualizations with the results, and permutation and cross-validation based tests to support the decision on the number of clusters.

Fit Maximum Entropy Optimality Theory models to data sets, generate the predictions made by such models for novel data, and compare the fit of different models using a variety of metrics. The package is described in Mayer, C., Tan, A., Zuraw, K. (in press) <https://sites.socsci.uci.edu/~cjmayer/papers/cmayer_et_al_maxent_ot_accepted.pdf>.

The Prize-Collecting Steiner Tree problem asks to find a subgraph connecting a given set of vertices with the most expensive nodes and least expensive edges. Since it is proven to be NP-hard, exact and efficient algorithm does not exist. This package provides convenient functionality for obtaining an approximate solution to this problem using loopy belief propagation algorithm.

Matches cases to controls based on genotype principal components (PC). In order to produce better results, matches are based on the weighted distance of PCs where the weights are equal to the % variance explained by that PC. A weighted Mahalanobis distance metric (Kidd et al. (1987) <DOI:10.1016/0031-3203(87)90066-5>) is used to determine matches.

Personalize drug regimens using individual pharmacokinetic (PK) and pharmacokinetic-pharmacodynamic (PK-PD) profiles. By combining therapeutic drug monitoring (TDM) data with a population model, posologyr offers accurate posterior estimates and helps compute optimal individualized dosing regimens. The empirical Bayes estimates are computed following the method described by Kang et al. (2012) <doi:10.4196/kjpp.2012.16.2.97>.

Estimation of mean squared prediction error of a small area predictor is provided. In particular, the recent method of Simple, Unified, Monte-Carlo Assisted approach for the mean squared prediction error estimation of small area predictor is provided. We also provide other existing methods of mean squared prediction error estimation such as jackknife method for the mixed logistic model.

This package provides a set of tools dedicated to modeling food web transfer based on an initial ground raster. It provides a directed acyclic graph structure for a set of rasters representing the flow of elements (e.g., food, energy, contaminants). It also includes tools for working with dispersal algorithms, enabling the combination of flux data with population movement.

This package provides indices and tools for directed acyclic graphs (DAGs), particularly DAG representations of intermittent streams. A detailed introduction to the package can be found in the publication: "Non-perennial stream networks as directed acyclic graphs: The R-package streamDAG" (Aho et al., 2023) <doi:10.1016/j.envsoft.2023.105775>, and in the introductory package vignette.

This package provides methods for detecting multiple change-points and segmenting univariate time series using Smallest Valid Partitioning (SVP). SVP searches for a partition with the smallest number of segments whose segments satisfy a user-defined or built-in validity test. Among partitions with the same number of segments, it minimizes a within-segment sum-of-squared-errors criterion.

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>.

Download, cache, and analyze census datasets and demographic statistics from Senegal. Datasets are sourced from public census releases provided by the Agence Nationale de la Statistique et de la Demographie (ANSD) <https://www.ansd.sn> and hosted on GitHub releases <https://github.com/Amady01/sencus>. Also provides tools to search through variable dictionaries and load tabular demographic indicators.

This package implements Bayesian inference in accelerated failure time (AFT) models for right-censored survival times assuming a log-logistic distribution. Details of the variational Bayes algorithms, with and without shared frailty, are described in Xian et al. (2024) <doi:10.1007/s11222-023-10365-6> and Xian et al. (2024) <doi:10.48550/arXiv.2408.00177>, respectively.

An interface to access data from Substack publications via API. Users can fetch the latest, top, search for specific posts, or retrieve a single post by its slug. This functionality is useful for developers and researchers looking to analyze Substack content or integrate it into their applications. For more information, visit the API documentation at <https://substackapi.dev/introduction>.

This package provides exact analytical algorithms for computing optimum sample allocations in stratified sampling. Supports classical Neyman-Tschuprow allocation, minimum-cost allocation under a variance constraint, and multi-domain allocation with controlled precision. Handles lower and upper bounds, cost constraints, and multiple domains. Includes helper functions for variance computation, allocation summaries, rounding, and example datasets for testing and benchmarking.

This package provides reusable building blocks for research packages across matrix representation, numerical computation, neighborhood evaluation, controlled execution, and runtime interoperability. Core tools preserve declared sparse semantics, expose dense-memory and output boundaries, standardize neighborhood and classification results, and align serial and parallel result and error behavior. Additional helpers support structured messages, optional dependency checks, and common statistical workflows.

This package provides functions for estimating times of common ancestry and molecular clock rates of evolution using a variety of evolutionary models, parametric and nonparametric bootstrap confidence intervals, methods for detecting outlier lineages, root-to-tip regression, and a statistical test for selecting molecular clock models. For more details see Volz and Frost (2017) <doi:10.1093/ve/vex025>.

Data structures and methods to work with web tracking data. The functions cover data preprocessing steps, enriching web tracking data with external information and methods for the analysis of digital behavior as used in several academic papers (e.g., Clemm von Hohenberg et al., 2023 <doi:10.17605/OSF.IO/M3U9P>; Stier et al., 2022 <doi:10.1017/S0003055421001222>).

This package provides an R API and htmlwidget facilitating interactive visualization of spatial single-cell data with Vitessce. The R API contains classes and functions for loading single-cell data stored in compatible on-disk formats. The htmlwidget is a wrapper around the Vitessce JavaScript library and can be used in the Viewer tab of RStudio or Shiny apps.

The ACE file format is used in genomics to store contigs from sequencing machines. This tools converts it into FASTQ format. Both formats contain the sequence characters and their corresponding quality information. Unlike the FASTQ file, the ACE file stores the quality values numerically. The conversion algorithm uses the standard Sanger formula. The package facilitates insertion into pipelines, and content inspection.

This package provides a collection of tools to evaluate probability density functions, cumulative distribution functions, quantile functions and random numbers for truncated random variables. These functions are provided to also compute the expected value and variance. Q-Q plots can be produced. All the probability functions in the stats, stats4 and evd packages are automatically available for truncation.