ENA (Shaffer, D. W. (2017) Quantitative Ethnography. ISBN: 0578191687) is a method used to identify meaningful and quantifiable patterns in discourse or reasoning. ENA moves beyond the traditional frequency-based assessments by examining the structure of the co-occurrence, or connections in coded data. Moreover, compared to other methodological approaches, ENA has the novelty of (1) modeling whole networks of connections and (2) affording both quantitative and qualitative comparisons between different network models. Shaffer, D.W., Collier, W., & Ruis, A.R. (2016).

RSound allows you to send audio from an application and transfer it directly to a different computer on your LAN network. It is an audio daemon with a much different focus than most other audio daemons.

This package predicts functional relevance of protein-protein interactions based on functional annotations such as Human Protein Ontology and Gene Ontology, and prioritizes genes based on network topology, functional scores and a path search algorithm.

This package discovers differential features in hetero- and homogeneous omic data by a two-step method including subsampling LIMMA and NSCA. DECO reveals feature associations to hidden subclasses not exclusively related to higher deregulation levels.

reproc (Redirected Process) is a C/C++ library that simplifies starting, stopping and communicating with external programs. The main use case is executing command line applications directly from C or C++ code and retrieving their output.

ICGE is a package that helps to estimate the number of real clusters in data as well as to identify atypical units. The underlying methods are based on distances rather than on unit x variables.

The brew package implements a templating framework for mixing text and R code for report generation. The template syntax is similar to PHP, Ruby's erb module, Java Server Pages, and Python's psp module.

ACDm is a package for Autoregressive Conditional Duration (ACD, Engle and Russell, 1998) models. It creates trade, price or volume durations from transactions (tic) data, performs diurnal adjustments, fits various ACD models and tests them.

This package provides functions related to L-moments: computation of L-moments and trimmed L-moments of distributions and data samples; parameter estimation; L-moment ratio diagram; plot vs. quantiles of an extreme-value distribution.

This package implements a data structure similar to hashes in Perl and dictionaries in Python but with a purposefully R flavor. For objects of appreciable size, access using hashes outperforms native named lists and vectors.

This package provides a compositional mediation model for continuous outcome and binary outcomes to deal with mediators that are compositional data. Lin, Ziqiang et al. (2022) <doi:10.1016/j.jad.2021.12.019>.

This package provides a collection of cardiovascular research datasets and analytical tools, including methods for cardiovascular procedural data, such as electrocardiography, echocardiography, and catheterization data. Additional methods exist for analysis of procedural billing codes.

Implement weighted higher-order initialization and angle-based iteration for multi-way spherical clustering under degree-corrected tensor block model. See reference Jiaxin Hu and Miaoyan Wang (2023) <doi:10.1109/TIT.2023.3239521>.

Implementation of the Density Ratio Permutation Test for testing the goodness-of-fit of a hypothesised ratio of two densities, as described in Bordino and Berrett (2025) <doi:10.48550/arXiv.2505.24529>.

This package provides a key-value dictionary data structure based on R6 class which is designed to be similar usages with other languages dictionary (e.g. Python') with reference semantics and extendabilities by R6.

This package provides a simple tool for the bulk creation and testing of parametric survival models. Simply provide fssg with a formula and some data, and let it identify the best distributions for you.

This package provides tools for downloading and analyzing floristic quality assessment data. See Freyman et al. (2015) <doi:10.1111/2041-210X.12491> for more information about floristic quality assessment and the associated database.

Visualize as flow diagrams the logic of functions, expressions or scripts in a static way or when running a call, visualize the dependencies between functions or between modules in a shiny app, and more.

Robust multiple or multivariate linear regression, nonparametric regression on orthogonal components, classical or robust partial least squares models as described in Bilodeau, Lafaye De Micheaux and Mahdi (2015) <doi:10.18637/jss.v065.i01>.

Routines for log-linear models of incomplete contingency tables, including some latent class models, via EM and Fisher scoring approaches. Allows bootstrapping. See Espeland and Hui (1987) <doi:10.2307/2531553> for general approach.

Estimation of high-dimensional multi-response regression with heterogeneous noises under Heterogeneous group square-root Lasso penalty. For details see: Ren, Z., Kang, Y., Fan, Y. and Lv, J. (2018)<arXiv:1606.03803>.

This package provides a set of routines to quickly download and import the HUGO Gene Nomenclature Committee (HGNC) data set on mapping of gene symbols to gene entries in other genomic databases or resources.

Generalised linear models via the iteratively reweighted least squares algorithm. The functions perform logistic, Poisson and Gamma regression (ISBN:9780412317606), either for a single model or many regression models in a column-wise fashion.

This package provides a collection of personal helper functions to avoid redundancy in the spirit of the "Don't repeat yourself" principle of software development (<https://en.wikipedia.org/wiki/Don%27t_repeat_yourself>).