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Package Name Access Summary Updated
r-reportfactory public Provides an infrastructure for handling multiple R Markdown reports, including automated curation and time-stamping of outputs, parameterisation and provision of helper functions to manage dependencies. 2025-09-22
r-whitening public Implements the whitening methods (ZCA, PCA, Cholesky, ZCA-cor, and PCA-cor) discussed in Kessy, Lewin, and Strimmer (2018) "Optimal whitening and decorrelation", <doi:10.1080/00031305.2016.1277159>, as well as the whitening approach to canonical correlation analysis allowing negative canonical correlations described in Jendoubi and Strimmer (2019) "A whitening approach to probabilistic canonical correlation analysis for omics data integration", <doi:10.1186/s12859-018-2572-9>. 2025-09-22
r-nsprcomp public Two methods for performing a constrained principal component analysis (PCA), where non-negativity and/or sparsity constraints are enforced on the principal axes (PAs). The function 'nsprcomp' computes one principal component (PC) after the other. Each PA is optimized such that the corresponding PC has maximum additional variance not explained by the previous components. In contrast, the function 'nscumcomp' jointly computes all PCs such that the cumulative variance is maximal. Both functions have the same interface as the 'prcomp' function from the 'stats' package (plus some extra parameters), and both return the result of the analysis as an object of class 'nsprcomp', which inherits from 'prcomp'. See <https://sigg-iten.ch/learningbits/2013/05/27/nsprcomp-is-on-cran/> and Sigg et al. (2008) <doi:10.1145/1390156.1390277> for more details. 2025-09-22
r-fwdselect public A simple method to select the best model or best subset of variables using different types of data (binary, Gaussian or Poisson) and applying it in different contexts (parametric or non-parametric). 2025-09-22
r-neuralnet public Training of neural networks using backpropagation, resilient backpropagation with (Riedmiller, 1994) or without weight backtracking (Riedmiller and Braun, 1993) or the modified globally convergent version by Anastasiadis et al. (2005). The package allows flexible settings through custom-choice of error and activation function. Furthermore, the calculation of generalized weights (Intrator O & Intrator N, 1993) is implemented. 2025-09-22
r-geomtextpath public A 'ggplot2' extension that allows text to follow curved paths. Curved text makes it easier to directly label paths or neatly annotate in polar co-ordinates. 2025-09-22
r-qlcmatrix public Extension of the functionality of the Matrix package for using sparse matrices. Some of the functions are very general, while other are highly specific for special data format as used for quantitative language comparison (QLC). 2025-09-22
r-embed public Predictors can be converted to one or more numeric representations using a variety of methods. Effect encodings using simple generalized linear models <arXiv:1611.09477> or nonlinear models <arXiv:1604.06737> can be used. There are also functions for dimension reduction and other approaches. 2025-09-22
ngram public N-Gram modeling 2025-09-22
openinference-instrumentation-openai public OpenInference OpenAI Instrumentation 2025-09-22
pyroaring public An efficient and light-weight ordered set of 32-bit integers 2025-09-22
typedload public Load and dump data from json-like format into typed data structures 2025-09-22
r-lightgbm public Tree based algorithms can be improved by introducing boosting frameworks. 'LightGBM' is one such framework, based on Ke, Guolin et al. (2017) <https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision>. This package offers an R interface to work with it. It is designed to be distributed and efficient with the following advantages: 1. Faster training speed and higher efficiency. 2. Lower memory usage. 3. Better accuracy. 4. Parallel learning supported. 5. Capable of handling large-scale data. In recognition of these advantages, 'LightGBM' has been widely-used in many winning solutions of machine learning competitions. Comparison experiments on public datasets suggest that 'LightGBM' can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. In addition, parallel experiments suggest that in certain circumstances, 'LightGBM' can achieve a linear speed-up in training time by using multiple machines. 2025-09-22
wandb public A CLI and library for interacting with the Weights and Biases API. 2025-09-22
r-iccbeta public A function and vignettes for computing an intraclass correlation described in Aguinis & Culpepper (2015) <doi:10.1177/1094428114563618>. This package quantifies the share of variance in a dependent variable that is attributed to group heterogeneity in slopes. 2025-09-22
r-glmtrans public Transfer Learning under Regularized Generalized Linear Models. 2025-09-22
r-fasttime public Fast functions for timestamp manipulation that avoid system calls and take shortcuts to facilitate operations on very large data. 2025-09-22
certbot-dns-nsone public NS1 DNS Authenticator plugin for Certbot 2025-09-22
certbot-dns-dnsmadeeasy public DigitalOcean DNS Authenticator plugin for Certbot 2025-09-22
samgeo public A Python package for segmenting geospatial data with the Segment Anything Model (SAM) 2025-09-22
segment-geospatial public A Python package for segmenting geospatial data with the Segment Anything Model (SAM) 2025-09-22
r-support public The 'support' package provides the functions sp() and sp_seq() for computing the support points in Mak and Joseph (2018) <DOI:10.1214/17-AOS1629>. Support points can be used as a representative sample of a desired distribution, or a representative reduction of a big dataset (e.g., an "optimal" thinning of Markov-chain Monte Carlo sample chains). This work was supported by USARO grant W911NF-14-1-0024 and NSF DMS grant 1712642. 2025-09-22
certbot-dns-cloudflare public Cloudflare DNS Authenticator plugin for Certbot 2025-09-22
r-ottr public An R autograding extension for Otter-Grader (<https://otter-grader.readthedocs.io>). It supports grading R scripts, R Markdown documents, and R Jupyter Notebooks. 2025-09-22
r-spthin public A set of functions that can be used to spatially thin species occurrence data. The resulting thinned data can be used in ecological modeling, such as ecological niche modeling. 2025-09-22

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