This package provides a Wrapper around the SVDLIBC library for (truncated) singular value decomposition of a sparse matrix. Currently, only sparse real matrices in Matrix package format are supported.

This package provides the functionality to set configuration options on a per-package basis. Options set by a given package only apply to that package, other packages are unaffected.

This package provides traits which define the functionality of block ciphers and stream ciphers. See RustCrypto/block-ciphers and RustCrypto/stream-ciphers for algorithm implementations which use these traits.

This package provides traits which define the functionality of block ciphers and stream ciphers. See RustCrypto/block-ciphers and RustCrypto/stream-ciphers for algorithm implementations which use these traits.

This package provides traits which define the functionality of block ciphers and stream ciphers. See RustCrypto/block-ciphers and RustCrypto/stream-ciphers for algorithm implementations which use these traits.

This package lets you find the difference between two instances of any data structure. Supports Collections, Strings, Maps, etc. Uses LCS where applicable. Also supports derive via `diffus-derive`.

This package provides a utility library intended at providing configurable reader macros for common tasks such as accessors, hash-tables, sets, uiop:run-program, arrays and a few others.

Implemented fast and memory-efficient Notch-filter, Welch-periodogram, discrete wavelet spectrogram for minutes of high-resolution signals, fast 3D convolution, image registration, 3D mesh manipulation; providing fundamental toolbox for intracranial Electroencephalography (iEEG) pipelines. Documentation and examples about RAVE project are provided at <https://rave.wiki>, and the paper by John F. Magnotti, Zhengjia Wang, Michael S. Beauchamp (2020) <doi:10.1016/j.neuroimage.2020.117341>; see citation("ravetools") for details.

Detecting outliers using robust methods, i.e. the Median Absolute Deviation (MAD) for univariate outliers; Leys, Ley, Klein, Bernard, & Licata (2013) <doi:10.1016/j.jesp.2013.03.013> and the Mahalanobis-Minimum Covariance Determinant (MMCD) for multivariate outliers; Leys, C., Klein, O., Dominicy, Y. & Ley, C. (2018) <doi:10.1016/j.jesp.2017.09.011>. There is also the more known but less robust Mahalanobis distance method, only for comparison purposes.

Infer log-linear Poisson Graphical Model with an auxiliary data set. Hot-deck multiple imputation method is used to improve the reliability of the inference with an auxiliary dataset. Standard log-linear Poisson graphical model can also be used for the inference and the Stability Approach for Regularization Selection (StARS) is implemented to drive the selection of the regularization parameter. The method is fully described in <doi:10.1093/bioinformatics/btx819>.

Process phylogenetic trees with tropical support vector machine and principal component analysis defined with tropical geometry. Details about tropical support vector machine are available in : Tang, X., Wang, H. & Yoshida, R. (2020) <arXiv:2003.00677>. Details about tropical principle component analysis are available in : Page, R., Yoshida, R. & Zhang L. (2020) <doi:10.1093/bioinformatics/btaa564> and Yoshida, R., Zhang, L. & Zhang, X. (2019) <doi:10.1007/s11538-018-0493-4>.

This package provides fast algorithms for the Theil-Sen estimator, Siegel's repeated median slope estimator, and Passing-Bablok regression. The implementation is based on algorithms by Dillencourt et al. (1992) <doi:10.1142/S0218195992000020> and Matousek et al. (1998) <doi:10.1007/PL00009190>. The implementations are detailed in Raymaekers (2023) <doi:10.32614/RJ-2023-012> and Raymaekers J., Dufey F. (2022) <arXiv:2202.08060>. All algorithms run in quasilinear time.

Bindings for all JS global objects and functions in all JS environments like Node.js and browsers, built on #[wasm_bindgen] using the wasm-bindgen crate.

This package provides a collection of tools for antitrust practitioners, including the ability to calibrate different consumer demand systems and simulate the effects of mergers under different competitive regimes.

This package provides functions to calculate the assortment of vertices in social networks. This can be measured on both weighted and binary networks, with discrete or continuous vertex values.

Making probabilistic projections of life expectancy for all countries of the world, using a Bayesian hierarchical model <doi:10.1007/s13524-012-0193-x>. Subnational projections are also supported.

Fits Bayesian grouped weighted quantile sum (BGWQS) regressions for one or more chemical groups with binary outcomes. Wheeler DC et al. (2019) <doi:10.1016/j.sste.2019.100286>.

Visualize the connectedness of factors in two-way tables. Perform two-way filtering to improve the degree of connectedness. See Weeks & Williams (1964) <doi:10.1080/00401706.1964.10490188>.

This package provides a collection of easy-to-use functions for creating visualizations of compositional data using ggplot2'. Includes support for common plotting techniques in compositional data analysis.

Generation of different Christmas cards, most of them being animated. Most of the cards can be generated in three languages (English, Catalan and Spanish). The collection started in 2009.

Call the DeOldify <https://github.com/jantic/DeOldify> image colorization API on DeepAI'<https://deepai.org/machine-learning-model/colorizer> to colorize black and white images.

Distributed Online Goodness-of-Fit Test can process the distributed datasets. The philosophy of the package is described in Guo G.(2024) <doi:10.1016/j.apm.2024.115709>.

Easily create descriptive and comparative tables. It makes use and integrates directly with the tidyverse family of packages, and pipes. Tables are produced as (nested) dataframes for easy manipulation.

This package provides data sets and R Codes for E.R. Williams, C.E. Harwood and A.C. Matheson (2023). Experimental Design and Analysis for Tree Improvement, CSIRO Publishing.