This package provides a single method implementing multiple approaches to generate pseudo-random vectors whose components sum up to one (see, e.g., Maziero (2015) <doi:10.1007/s13538-015-0337-8>). The components of such vectors can for example be used for weighting objectives when reducing multi-objective optimisation problems to a single-objective problem in the socalled weighted sum scalarisation approach.

This is a simple package which provides a function that boosts pre-ready or custom-made classifiers. Package uses Discrete AdaBoost (<doi:10.1006/jcss.1997.1504>) and Real AdaBoost (<doi:10.1214/aos/1016218223>) for two class, SAMME (<doi:10.4310/SII.2009.v2.n3.a8>) and SAMME.R (<doi:10.4310/SII.2009.v2.n3.a8>) for multiclass classification.

rpi-imager is graphical utility to easily provision and flash a memory card with an operating system image suitable for the Raspberry Pi single board computer.

R and C++ functions to perform exact and approximate optimal transport. All C++ methods can be linked to other R packages via their header files.

Datasets and functions for the book "Initiation à la Statistique avec R", F. Bertrand and M. Maumy-Bertrand (2022, ISBN:978-2100782826 Dunod, fourth edition).

Accelerate the process from clinical data to medical publication, including clinical data cleaning, significant result screening, and the generation of publish-ready tables and figures.

Quantify variability (such as confidence interval) of fertilizer response curves and optimum fertilizer rates using bootstrapping residuals with several popular non-linear and linear models.

This package provides a replacement for dplyr::na_if(). Allows you to specify multiple values to be replaced with NA using a single function.

This package provides a full set of fast data manipulation tools with a tidy front-end and a fast back-end using collapse and cheapr'.

This package provides a simple way to interact with and extract data from the official Google Knowledge Graph API <https://developers.google.com/knowledge-graph/>.

Estimation of partial correlation matrix using ridge penalty followed by thresholding and reestimation. Under multivariate Gaussian assumption, the matrix constitutes an Gaussian graphical model (GGM).

An almost direct port of the python humanize package <https://github.com/jmoiron/humanize>. This package contains utilities to convert values into human readable forms.

This package provides a seamless bridge between keras and the tidymodels frameworks. It allows for the dynamic creation of parsnip model specifications for keras models.

This package contains data sets to accompany the book: Lazic SE (2016). "Experimental Design for Laboratory Biologists: Maximising Information and Improving Reproducibility". Cambridge University Press.

Allows the estimation and downstream statistical analysis of the mitochondrial DNA Heteroplasmy calculated from single-cell datasets <https://github.com/ScialdoneLab/MitoHEAR/tree/master>.

Functionality to estimate relative risks, risk differences, and partial effects from mixed model. Marginalisation over random effect terms is accomplished using Markov Chain Monte Carlo.

Optimization for nonlinear objective and constraint functions. Linear or nonlinear equality and inequality constraints are allowed. It accepts the input parameters as a constrained matrix.

Density, distribution function, quantile function and random generation for the Nakagami distribution of Nakagami (1960) <doi:10.1016/B978-0-08-009306-2.50005-4>.

Estimation, hypothesis tests, and variable selection in partially linear single-index models. Please see H. (2010) at <doi:10.1214/10-AOS835> for more details.

It estimates power and sample size for Partial Least Squares-based methods described in Andreella, et al., (2024), <doi:10.48550/arXiv.2403.10289>.

This package provides a simple function to bind a piped object to a placeholder symbol to enable complex function evaluation with the base R |> pipe.

Programmatic access to the PGS Catalog. This package provides easy access to PGS Catalog data by accessing the REST API <https://www.pgscatalog.org/rest/>.

Surveys to collect employment data so as to obtain data estimates on the number of employed people, the number of unemployed, and other employment indicators.

This package contains gene-level counts for a collection of public scRNA-seq datasets, provided as SingleCellExperiment objects with cell- and gene-level metadata.