Read, process, and export DICOM and DICOM-RT files (structures, dosimetry, imagery) for medical physics and clinical research, with patient-oriented 2D-3D visualization.

This package provides a collection of functions to manage, to investigate and to analyze data sets of financial assets from different points of view.

This package provides a simple and time saving multiple linear regression function (OLS) with interpretation, optional bootstrapping, effect size calculation and all tested requirements.

Pull data from the Impect Customer API <https://glossary.impect.com/api-design>. The package can retrieve data such as events or match sums.

All datasets and functions used in the german book "Statistik mit R und RStudio" by grosse Schlarmann (2010-2024) <https://www.produnis.de/R/>.

Allow to run jshint on JavaScript files with a R command or a RStudio addin. The report appears in the RStudio viewer pane.

This package provides a largish collection of example datasets, including several classics. Many of these datasets are well suited for regression, classification, and visualization.

This package implements a logistic box-cox model. This model is fully described in Xing, L. et al. (2021) <doi:10.1002/cjs.11587>.

Repairs malformed JSON strings, particularly those generated by Large Language Models. Handles missing quotes, trailing commas, unquoted keys, and other common JSON syntax errors.

This package contains the datasets for use with the book Salvan, Sartori and Pace (2020, ISBN:978-88-470-4002-1) "Modelli Lineari Generalizzati".

An object that supports automatic differentiation of matrix- and multidimensional-valued functions with respect to multidimensional independent variables. Automatic differentiation is via forward accumulation'.

Interface to OpenStreetMap API for fetching and saving data from/to the OpenStreetMap database (<https://wiki.openstreetmap.org/wiki/API_v0.6>).

This package provides several data sets and functions to accompany the book "Population Genetics with R: An Introduction for Life Scientists" (2021, ISBN:9780198829546).

Statistical power analysis for designs including t-tests, correlations, multiple regression, ANOVA, mediation, and logistic regression. Functions accompany Aberson (2019) <doi:10.4324/9781315171500>.

Datasets for the book, A Guide to QTL Mapping with R/qtl. Broman and Sen (2009) <doi:10.1007/978-0-387-92125-9>.

Sequential triangular test for the arithmetic mean in one- and two- samples, proportions in one- and two-samples, and the Pearson's correlation coefficient.

Data sets from Ramsey, F.L. and Schafer, D.W. (2002), "The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed)", Duxbury.

Define general templates with tags that can be replaced by content depending on arguments and objects to modify the final output of the document.

Helper functions for TUFLOW FV models. Current functionality includes reading in and plotting output POINTS files and generating initial conditions based on point observations.

Access Google Trends information. This package provides a tidy wrapper to the gtrendsR package. Use four spaces when indenting paragraphs within the Description.

This package provides tools to perform random forest consensus clustering of different data types. The package is designed to accept a list of matrices from different assays, typically from high-throughput molecular profiling so that class discovery may be jointly performed. For references, please see Tao Shi & Steve Horvath (2006) <doi:10.1198/106186006X94072> & Monti et al (2003) <doi:10.1023/A:1023949509487> .

NCL (NCAR Command Language) is one of the most popular spatial data mapping tools in meteorology studies, due to its beautiful output figures with plenty of color palettes designed by experts <https://www.ncl.ucar.edu/index.shtml>. Here we translate all NCL color palettes into R hexadecimal RGB colors and provide color selection function, which will help users make a beautiful figure.

Insert/extract text "reminders" into/from function source code comments or as the "comment" attribute of any object. The former can be handy in development as reminders of e.g. argument requirements, expected objects in the calling environment, required options settings, etc. The latter can be used to provide information of the object and as simple manual "tooltips" for users, among other things.

This package implements safe policy learning under regression discontinuity designs with multiple cutoffs, based on Zhang et al. (2022) <doi:10.48550/arXiv.2208.13323>. The learned cutoffs are guaranteed to perform no worse than the existing cutoffs in terms of overall outcomes. The rdlearn package also includes features for visualizing the learned cutoffs relative to the baseline and conducting sensitivity analyses.