Basic statistical methods with some modifications for the course Statistical Methods at Federal University of Bahia (Brazil). All methods in this packages are explained in the text book of Montgomery and Runger (2010) <ISBN: 978-1-119-74635-5>.

This package provides an R interface for interacting with the Semestry TermTime services. It allows users to retrieve scheduling data from the API. see <https://github.com/vusaverse/vvtermtime/blob/main/openapi_7.7.0.pdf> for details.

This package provides methods for retrieving United States Geological Survey (USGS) water data using sequential and parallel processing (Bengtsson, 2022 <doi:10.32614/RJ-2021-048>). In addition to parallel methods, data wrangling and additional statistical attributes are provided.

Create presentations and display them inside the R REPL (Read-Eval-Print loop), aka the R console. Presentations can be written in RMarkdown or any other text format. A set of convenient navigation options as well as code evaluation during a presentation is provided. It is great for tech talks with live coding examples and tutorials. While this is not a replacement for standard presentation formats, it's old-school looks might just be what sets it apart. This project has been inspired by the REPLesent project for presentations in the Scala REPL'.

This package provides a rotatogram is a method of displaying an association which is axis non-dominant. This is achieved in two ways: First, the method of estimating the slope and intercept uses the least-products method rather than more typical least squared error for the "dependent" variable. The least products method has no "dependent" variable and is scale independent. Second, the plot is rotated such that the resulting regression line is vertical, reducing the suggestion that the vertical axis is the dominant one. The slope can be read relative to either axis equally.

An implementation of easy tools for outlier robust inference in two-stage least squares (2SLS) models. The user specifies a reference distribution against which observations are classified as outliers or not. After removing the outliers, adjusted standard errors are automatically provided. Furthermore, several statistical tests for the false outlier detection rate can be calculated. The outlier removing algorithm can be iterated a fixed number of times or until the procedure converges. The algorithms and robust inference are described in more detail in Jiao (2019) <https://drive.google.com/file/d/1qPxDJnLlzLqdk94X9wwVASptf1MPpI2w/view>.

Reproducibility is essential to the progress of research, yet achieving it remains elusive even in computational fields. Continuous Integration (CI) platforms offer a powerful way to launch automated workflows to check and document code, but often require considerable time, effort, and technical expertise to setup. We therefore developed the rworkflows suite to make robust CI workflows easy and freely accessible to all R package developers. rworkflows consists of 1) a CRAN/Bioconductor-compatible R package template, 2) an R package to quickly implement a standardised workflow, and 3) a centrally maintained GitHub Action.

Calculates the coverage of high-throughput short-reads against a genome of reference and summarizes it per feature of interest (e.g. exon, gene, transcript). The data can be normalized as RPKM or by the DESeq or edgeR package.

FISHalyseR provides functionality to process and analyse digital cell culture images, in particular to quantify FISH probes within nuclei. Furthermore, it extract the spatial location of each nucleus as well as each probe enabling spatial co-localisation analysis.

Shepherd-run is a script which assists in creating one-off shepherd services from the command line. It is meant to partially fill the void left by systemd-run, since GNU Guix uses GNU Shepherd as its system service manager.

Geometry shapes in R are typically represented by matrices (points, lines), with more complex shapes being lists of matrices (polygons). Geometries will convert various R objects into these shapes. Conversion functions are available at both the R level, and through Rcpp.

This package provides tools to infer the code style (which style rules are followed and which ones are not) from one package and use it to check another. This makes it easier to find and correct the most important problems first.

mlr3tuning implements methods for hyperparameter tuning, e.g. Grid Search, Random Search, or Simulated Annealing. Various termination criteria can be set and combined. The class AutoTuner provides a convenient way to perform nested resampling in combination with mlr3.

This package provides a wrapper around the C++ library polylabel from Mapbox, providing an efficient routine for finding the approximate pole of inaccessibility of a polygon, which usually serves as an excellent candidate for labeling of a polygon.

With the DiagrammeR package you can create, modify, analyze, and visualize network graph diagrams. The output can be incorporated into R Markdown documents, integrated with Shiny web apps, converted to other graph formats, or exported as image files.

This package provides Python'-style list comprehensions. List comprehension expressions use usual loops (for(), while() and repeat()) and usual if() as list producers. In many cases it gives more concise notation than standard "*apply + filter" strategy.

Perform sparse estimation of a Gaussian graphical model (GGM) with node aggregation through variable clustering. Currently, the package implements the clusterpath estimator of the Gaussian graphical model (CGGM) (Touw, Alfons, Groenen & Wilms, 2025; <doi:10.48550/arXiv.2407.00644>).

Easily install and load all packages and functions used in CourseKata courses. Aid teaching with helper functions and augment generic functions to provide cohesion between the network of packages. Learn more about CourseKata at <https://www.coursekata.org>.

Modifies dot plots to have different sizes of dots mimicking violin plots and identifies modes or peaks for them based on frequency and kernel density estimates (Rosenblatt, 1956) <doi:10.1214/aoms/1177728190> (Parzen, 1962) <doi:10.1214/aoms/1177704472>.

This package provides methods for dividing data into groups. Create balanced partitions and cross-validation folds. Perform time series windowing and general grouping and splitting of data. Balance existing groups with up- and downsampling or collapse them to fewer groups.

This package performs recursive partitioning of linear and nonlinear mixed effects models, specifically for longitudinal data. The package is an extension of the original longRPart package by Stewart and Abdolell (2013) <https://cran.r-project.org/package=longRPart>.

The NetCoupler algorithm identifies potential direct effects of correlated, high-dimensional variables formed as a network with an external variable. The external variable may act as the dependent/response variable or as an independent/predictor variable to the network.

This package provides methods for generating, exploring and executing seamless Phase II-III designs of Lai, Lavori and Shih using generalized likelihood ratio statistics. Includes pdf and source files that describe the entire R implementation with the relevant mathematical details.

Miscellaneous functions for working with stars objects, mainly single-band rasters. Currently includes functions for: (1) focal filtering, (2) detrending of Digital Elevation Models, (3) calculating flow length, (4) calculating the Convergence Index, (5) calculating topographic aspect and topographic slope.