This package provides computational support for flow over weirs, such as sharp-crested, broad-crested, and embankments. Initially, the package supports broad- and sharp-crested weirs.

This package provides functions for calculating the fetch (length of open water distance along given directions) and estimating wave energy from wind and wave monitoring data.

This package calculates probabilistic pathway scores using gene expression data. Gene expression values are aggregated into pathway-based scores using Bayesian network representations of biological pathways.

The atSNP package performs affinity tests of motif matches with the SNP (single nucleotide polymorphism) or the reference genomes and SNP-led changes in motif matches.

This package provides a package to analyze oligonucleotide arrays (expression/SNP/tiling/exon) at probe-level. It currently supports Affymetrix (CEL files) and NimbleGen arrays (XYS files).

This package provides useful functions to edit ggplot object (e.g., setting fonts for theme and layers, adding rounded rectangle as background for each of the legends).

Designed to enable simultaneous substitution in strings in a safe fashion. Safe means it does not rely on placeholders (which can cause errors in same length matches).

This package provides methods and functions for fitting maximum likelihood models in R. This package modifies and extends the mle classes in the stats4 package.

This package provides fast and memory efficient methods for truncated singular and eigenvalue decompositions, as well as for principal component analysis of large sparse or dense matrices.

This package provides functions for latent class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive Bayes classifier, and more.

This package provides a set of tools for working with Romanian personal numeric codes. The core is a validation function which applies several verification criteria to assess the validity of numeric codes. This is accompanied by functionality for extracting the different components of a personal numeric code. A personal numeric code is issued to all Romanian residents either at birth or when they obtain a residence permit.

Embeds sources and headers from Tina's Random Number Generator ('TRNG') C++ library. Exposes some functionality for easier access, testing and benchmarking into R. Provides examples of how to use parallel RNG with RcppParallel'. The methods and techniques behind TRNG are illustrated in the package vignettes and examples. Full documentation is available in Bauke (2021) <https://github.com/rabauke/trng4/blob/v4.23.1/doc/trng.pdf>.

Integrates population dynamics and dispersal into a mechanistic virtual species simulator. The package can be used to study the effects of environmental change on population growth and range shifts. It allows for simple and straightforward definition of population dynamics (including positive density dependence), extensive possibilities for defining dispersal kernels, and the ability to generate virtual ecologist data. Learn more about the rangr at <https://docs.ropensci.org/rangr/>.

Routine for fitting regression models for binary rare events with linear and nonlinear covariate effects when using the quantile function of the Generalized Extreme Value random variable.

Two-step feature-based clustering method designed for micro panel (longitudinal) data with the artificial panel data generator. See Sobisek, Stachova, Fojtik (2018) <arXiv:1807.05926>.

This package contains Data frames and functions used in the book "Design and Analysis of Experiments with R", Lawson(2015) ISBN-13:978-1-4398-6813-3.

Extra strength glue for data-driven templates. String interpolation for Shiny apps or R Markdown and knitr'-powered Quarto documents, built on the glue and whisker packages.

Given the values of sampled units and selection probabilities the desraj function in the package computes the estimated value of the total as well as estimated variance.

Accompanying package of the book Financial Risk Modelling and Portfolio Optimisation with R', second edition. The data sets used in the book are contained in this package.

This package provides methods from the paper: Pena, EA and Slate, EH, "Global Validation of Linear Model Assumptions," J. American Statistical Association, 101(473):341-354, 2006.

This package implements GINA-X, a genome-wide iterative fine-mapping method designed for non-Gaussian traits. It supports the identification of credible sets of genetic variants.

Data files and a few functions used in the book Linear Models and Regression with R: An Integrated Approach by Debasis Sengupta and Sreenivas Rao Jammalamadaka (2019).

Tests of comparison of two or more survival curves. Allows for comparison of more than two survival curves whether the proportional hazards hypothesis is verified or not.

This package provides tools that allow developers to write functions for prediction error estimation with minimal programming effort and assist users with model selection in regression problems.