This package performs penalized quantile regression with LASSO, elastic net, SCAD and MCP penalty functions including group penalties. In addition, offers a group penalty that provides consistent variable selection across quantiles. Provides a function that automatically generates lambdas and evaluates different models with cross validation or BIC, including a large p version of BIC. Below URL provides a link to article in the R Journal.

Implementation of the MEthod based on the Removal Effects of Criteria - MEREC- a new objective weighting method for determining criteria weights for Multiple Criteria Decision Making problems, created by Mehdi Keshavarz-Ghorabaee (2021) <doi:10.3390/sym13040525>. Given a decision matrix, the function return the Merec´s weight vector and all intermediate matrix/vectors used to calculate it.

ROSE (RObust Semiparametric Efficient) random forests for robust semiparametric efficient estimation in partially parametric models (containing generalised partially linear models). Details can be found in the paper by Young and Shah (2024) <doi:10.48550/arXiv.2410.03471>.

Streamlines the creation of reproducible analytical pipelines using default.nix expressions generated via the rix package for reproducibility. Define derivations in R', Python or Julia', chain them into a composition of pure functions and build the resulting pipeline using Nix as the underlying end-to-end build tool. Functions to plot the pipeline as a directed acyclic graph are included, as well as functions to load and inspect intermediary results for interactive analysis. User experience heavily inspired by the targets package.

Implementation of Gibbs sampling algorithm for Bayesian Estimation of the Reduced Reparameterized Unified Model ('rrum'), described by Culpepper and Hudson (2017) <doi: 10.1177/0146621617707511>.

Robust parameter estimation and prediction of Gaussian stochastic process emulators. It allows for robust parameter estimation and prediction using Gaussian stochastic process emulator. It also implements the parallel partial Gaussian stochastic process emulator for computer model with massive outputs See the reference: Mengyang Gu and Jim Berger, 2016, Annals of Applied Statistics; Mengyang Gu, Xiaojing Wang and Jim Berger, 2018, Annals of Statistics.

This package provides a collection of personal functions designed to simplify and streamline common R programming tasks. This package provides reusable tools and shortcuts for frequently used calculations and workflows.

Integrates the Groovy scripting language with the R Project for Statistical Computing.

Efficient reading of raw markdown tables into tibbles. Designed to accept content from strings, files, and URLs with the ability to extract and read multiple tables from markdown for analysis.

This package provides a lightweight implementation of the geomorphon terrain form classification algorithm of Jasiewicz and Stepinski (2013) <doi:10.1016/j.geomorph.2012.11.005> based largely on the GRASS GIS r.geomorphon module. This implementation employs a novel algorithm written in C++ and RcppParallel'.

Adds the MIxing-Data Sampling (MIDAS, Ghysels et al. (2007) <doi:10.1080/07474930600972467>) components to a variety of GARCH and MEM (Engle (2002) <doi:10.1002/jae.683>, Engle and Gallo (2006) <doi:10.1016/j.jeconom.2005.01.018>, and Amendola et al. (2024) <doi:10.1016/j.seps.2023.101764>) models, with the aim of predicting the volatility with additional low-frequency (that is, MIDAS) terms. The estimation takes place through simple functions, which provide in-sample and (if present) and out-of-sample evaluations. rumidas also offers a summary tool, which synthesizes the main information of the estimated model. There is also the possibility of generating one-step-ahead and multi-step-ahead forecasts.

This package provides a collection of functions for computing "r-values" from various kinds of user input such as MCMC output or a list of effect size estimates and associated standard errors. Given a large collection of measurement units, the r-value, r, of a particular unit is a reported percentile that may be interpreted as the smallest percentile at which the unit should be placed in the top r-fraction of units.

This package provides R bindings for Tabulator JS <https://tabulator.info/>. Makes it a breeze to create highly customizable interactive tables in rmarkdown documents and shiny applications. It includes filtering, grouping, editing, input validation, history recording, column formatters, packaged themes and more.

R interface to access prices and market data with the Bloomberg Data License service from <https://www.bloomberg.com/professional/product/data-license/>. As a prerequisite, a valid Data License from Bloomberg is needed together with the corresponding SFTP credentials and whitelisting of the IP from which accessing the service. This software and its author are in no way affiliated, endorsed, or approved by Bloomberg or any of its affiliates. Bloomberg is a registered trademark.

Efficient diffusing of content across function documentations. Sections, parameters or dot parameters are extracted from function documentations and turned into valid Rd character strings, which are ready to diffuse into the roxygen comments of another function by inserting inline code.

Studies of resilience in older adults employ a single-arm design where everyone experiences the stressor. The simplistic approach of regressing change versus baseline yields biased estimates due to regression-to-the-mean. This package provides a method to correct the bias. It also allows covariates to be included. The method implemented in the package is described in Varadhan, R., Zhu, J., and Bandeen-Roche, K (2024), Biostatistics 25(4): 1094-1111.

This package implements the RecMap MP2 construction heuristic <doi:10.1109/INFVIS.2004.57>. This algorithm draws maps according to a given statistical value, e.g., election results, population, or epidemiological data. The basic idea of the RecMap algorithm is that each map region, e.g., different countries, is represented by a rectangle. The area of each rectangle represents the statistical value provided as input to maintain zero cartographic error. Computationally intensive tasks are implemented in C++. The included vignette documents recmap algorithm usage.

Enhanced functionality for reactable in shiny applications, offering interactive and dynamic data table capabilities with ease. With reactable.extras', easily integrate a range of functions and components to enrich your shiny apps and facilitate user-friendly data exploration.

Perform robust estimation and inference in platform trials and other master protocol trials. Yuhan Qian, Yifan Yi, Jun Shao, Yanyao Yi, Gregory Levin, Nicole Mayer-Hamblett, Patrick J. Heagerty, Ting Ye (2025) <doi:10.48550/arXiv.2411.12944>.

This package provides an easy way to report the results of regression analysis, including: 1. Proportional hazards regression from function coxph of package survival'; 2. Conditional logistic regression from function clogit of package survival'; 3. Ordered logistic regression from function polr of package MASS'; 4. Binary logistic regression from function glm of package stats'; 5. Linear regression from function lm of package stats'; 6. Risk regression model for survival analysis with competing risks from function FGR of package riskRegression'; 7. Multilevel model from function lme of package nlme'.

This package implements an interface to Minecraft (Bedrock Edition) worlds. Supports the analysis and management of these worlds and game saves.

Inverse normal transformation (INT) based genetic association testing. These tests are recommend for continuous traits with non-normally distributed residuals. INT-based tests robustly control the type I error in settings where standard linear regression does not, as when the residual distribution exhibits excess skew or kurtosis. Moreover, INT-based tests outperform standard linear regression in terms of power. These tests may be classified into two types. In direct INT (D-INT), the phenotype is itself transformed. In indirect INT (I-INT), phenotypic residuals are transformed. The omnibus test (O-INT) adaptively combines D-INT and I-INT into a single robust and statistically powerful approach. See McCaw ZR, Lane JM, Saxena R, Redline S, Lin X. "Operating characteristics of the rank-based inverse normal transformation for quantitative trait analysis in genome-wide association studies" <doi:10.1111/biom.13214>.

The LabKey client library for R makes it easy for R users to load live data from a LabKey Server, <https://www.labkey.com/>, into the R environment for analysis, provided users have permissions to read the data. It also enables R users to insert, update, and delete records stored on a LabKey Server, provided they have appropriate permissions to do so.

This package provides access to the xylib C library for to import xy data from powder diffraction, spectroscopy and other experimental methods.