Designed to enhance data validation and management processes by employing a set of functions that read a set of rules from a CSV or Excel file and apply them to a dataset. Funded by the National Renewable Energy Laboratory and Possibility Lab, maintained by the Moore Institute for Plastic Pollution Research.

We consider the problem of estimating two isotonic regression curves g1* and g2* under the constraint that they are ordered, i.e. g1* <= g2*. Given two sets of n data points y_1, ..., y_n and z_1, ..., z_n that are observed at (the same) deterministic design points x_1, ..., x_n, the estimates are obtained by minimizing the Least Squares criterion L(a, b) = sum_i=1^n (y_i - a_i)^2 w1(x_i) + sum_i=1^n (z_i - b_i)^2 w2(x_i) over the class of pairs of vectors (a, b) such that a and b are isotonic and a_i <= b_i for all i = 1, ..., n. We offer two different approaches to compute the estimates: a projected subgradient algorithm where the projection is calculated using a PAVA as well as Dykstra's cyclical projection algorithm.

Overture Maps offers free and open geospatial map data sourced from various providers and standardized to a common schema. This tool allows you to download Overture Maps data for a specific region of interest and convert it to several different file formats. For more information, visit <https://overturemaps.org/download/>.

R Interface to ONNX - Open Neural Network Exchange <https://onnx.ai/>. ONNX provides an open source format for machine learning models. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types.

Bayesian reconstruction of who infected whom during past outbreaks using routinely-collected surveillance data. Inference of transmission trees using genotype, age specific social contacts, distance between cases and onset dates of the reported cases. (Robert A, Kucharski AJ, Gastanaduy PA, Paul P, Funk S. (2020) <doi:10.1098/rsif.2020.0084>).

Estimation of value and hedging strategy of call and put options, based on optimal hedging and Monte Carlo method, from Chapter 3 of Statistical Methods for Financial Engineering', by Bruno Remillard, CRC Press, (2013).

Functionality to handle and project lat-long coordinates, easily download background maps and add a correct scale bar to OpenStreetMap plots in any map projection.

Design and analysis of confirmatory adaptive clinical trials using the optimal conditional error framework according to Brannath and Bauer (2004) <doi:10.1111/j.0006-341X.2004.00221.x>. An extension to the optimal conditional error function using interim estimates as described in Brannath and Dreher (2024) <doi:10.48550/arXiv.2402.00814> and functions to ensure that the resulting conditional error function is non-increasing are also available.

Advanced forecasting algorithms for long-term energy demand at the national or regional level. The methodology is based on Grandón et al. (2024) <doi:10.1016/j.apenergy.2023.122249>; Zimmermann & Ziel (2024) <doi:10.1016/j.apenergy.2025.125444>. Real-time data, including power demand, weather conditions, and macroeconomic indicators, are provided through automated API integration with various institutions. The modular approach maintains transparency on the various model selection processes and encompasses the ability to be adapted to individual needs. oRaklE tries to help facilitating robust decision-making in energy management and planning.

This package provides a comprehensive set of helpers that streamline data transmission and processing, making it effortless to interact with the OpenAI API.

Aids in the analysis of genes influencing cancer survival by including a principal function, calculator(), which calculates the P-value for each provided gene under the optimal cutoff in cancer survival studies. Grounded in methodologies from significant works, this package references Therneau's survival package (Therneau, 2024; <https://CRAN.R-project.org/package=survival>) and the survival analysis extensions by Therneau and Grambsch (2000, ISBN 0-387-98784-3). It also integrates the survminer package by Kassambara et al. (2021; <https://CRAN.R-project.org/package=survminer>), enhancing survival curve visualizations with ggplot2'.

Create regression tables for publication. Currently supports lm', glm', survreg', and ivreg outputs.

Clinical reports generated by Oncomine Reporter software contain critical data in unstructured PDF format, making manual extraction time-consuming and error-prone. ORscraper provides a coherent suite of functions to automate this process, allowing researchers to parse reports, identify key biomarkers, extract genetic variant tables, and filter results. It also integrates with the NCBI ClinVar API <https://www.ncbi.nlm.nih.gov/clinvar/> to enrich extracted data.

Image analysis techniques for positron emission tomography (PET) that form part of the Rigorous Analytics bundle.

Ordinal patterns describe the dynamics of a time series by looking at the ranks of subsequent observations. By comparing ordinal patterns of two times series, Schnurr (2014) <doi:10.1007/s00362-013-0536-8> defines a robust and non-parametric dependence measure: the ordinal pattern coefficient. Functions to calculate this and a method to detect a change in the pattern coefficient proposed in Schnurr and Dehling (2017) <doi:10.1080/01621459.2016.1164706> are provided. Furthermore, the package contains a function for calculating the ordinal pattern frequencies. Generalized ordinal patterns as proposed by Schnurr and Fischer (2022) <doi:10.1016/j.csda.2022.107472> are also considered.

This package provides a solver for ompr based on the R Optimization Infrastructure ('ROI'). The package makes all solvers in ROI available to solve ompr models. Please see the ompr website <https://dirkschumacher.github.io/ompr/> and package docs for more information and examples on how to use it.

Connects to Google cloud vision <https://cloud.google.com/vision> to perform label detection and repurpose this feature for image classification.

An RStudio addin to assist with removing objects from the global environment. Features include removing objects according to name patterns and object type. During the course of an analysis, temporary objects are often created and this tool assists with removing them quickly. This can be useful when memory management within R is important.

This package provides tools for easy exploration of the world ocean atlas of the US agency National Oceanic and Atmospheric Administration (NOAA). It includes functions to extract NetCDF data from the repository and code to visualize several physical and chemical parameters of the ocean. A Shiny app further allows interactive exploration of the data. The methods for data collecting and quality checks are described in several papers, which can be found here: <https://www.ncei.noaa.gov/products/world-ocean-atlas>.

This package provides rectangular elements that can be dragged and resized over plots in shiny apps. This may be useful in applications where users need to mark regions on the plot for further input or processing.

Identify the optimal timing for new treatment initiation during multiple state disease transition, including multistate model fitting, simulation of mean residual lifetime for a given transition state, and estimation of confidence interval. The method is referred to de Wreede, L., Fiocco, M., & Putter, H. (2011) <doi:10.18637/jss.v038.i07>.

Evaluates the Owen Q-function for an integer value of the degrees of freedom, by applying Owen's algorithm (1965) <doi:10.1093/biomet/52.3-4.437>. It is useful for the calculation of the power of equivalence tests.

This package infers Boolean rules among cis-regulatory regions using paired chromatin accessibility and gene expression data at bulk and single-cell levels. Links regulatory regions to target genes, providing insights into gene regulation mechanisms.

Introduces optional types with some() and none, as well as match_with() from functional languages.