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This package implements a general framework for globally optimizing user-specified objective functionals over interpretable binary weight functions represented as sparse decision trees, called ROOT (Rashomon Set of Optimal Trees). It searches over candidate trees to construct a Rashomon set of near-optimal solutions and derives a summary tree highlighting stable patterns in the optimized weights. ROOT includes a built-in generalizability mode for identifying subgroups in trial settings for transportability analyses (Parikh et al. (2025) <doi:10.1080/01621459.2025.2495319>).
Randomization lists are an integral component of randomized clinical trials. randotools provides tools to easily create such lists.
This package provides a quantile regression method for multivariate data to find linear combinations of explanatory and response variables generalizing canonical correlation. The package consists of functions, rqcan() for fitting the coefficients, and summary.rqcan(), which calls a bootstrap function. For details, see the help files for rqcan() and summary.rqcan(), and the reference: Portnoy (2022) <doi:10.1016/j.jmva.2022.105071>.
Integrated open data fixtures used by the rmorie package for examples, vignettes, and tests. Contains snapshots of publicly available datasets from open-data portals built on the Comprehensive Knowledge Archive Network ('CKAN', <https://ckan.org/>), Socrata (<https://dev.socrata.com/>), and Opendatasoft (<https://www.huwise.com/>) (Chicago, New York City, Toronto, Vancouver, and others), Statistics Canada Canadian Centre for Justice and Community Safety Statistics ('CCJS') tables, a multi-agent-reviewed corpus of Ontario Special Investigations Unit ('SIU', <https://www.siu.on.ca/>) director's reports, and synthetic fixtures for unit tests. Also ships a small set of analyst-facing helpers for releasing aggregate statistics without re-identification risk: Laplace and Gaussian differential privacy mechanisms and k-anonymity, l-diversity, and cell suppression verifiers.
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.
This package provides canola-specific functions, processes and parameter sets used by canola model in the Agricultural Production Systems sIMulator ('APSIM') Next Generation. Includes tools for crop process calculations, parameter management and customisation, enabling users to explore, modify and apply canola model components.
This package provides functions for connecting to and interfacing with an Arduino or similar device. Functionality includes uploading of sketches, setting and reading digital and analog pins, and rudimentary servo control. This project is not affiliated with the Arduino company, <https://www.arduino.cc/>.
Offers functions for fetching JSON data from the US EPA Air Quality System (AQS) API with options to comply with the API rate limits. See <https://aqs.epa.gov/aqsweb/documents/data_api.html> for details of the AQS API.
Simplifies integration with Amazon Cognito (<https://aws.amazon.com/cognito/>) for R developers, enabling easy management of user authentication, registration, and password flows.
Interactively build and explore public transit routes with r5r package via a graphical user interface in a shiny app. The underlying routing methods are described in Pereira et al. (2021) <doi:10.32866/001c.21262>.
Implementation of robust sparse PCA using the ROSPCA algorithm of Hubert et al. (2016) <DOI:10.1080/00401706.2015.1093962>.
Screens all .R', .Rmd', and .qmd files to extract the name of packages used in a project. This package detects packages called with library(foo)', require(foo)', foo::bar() and use("foo", "bar") and adds these dependencies in the DESCRIPTION file in the sections Depends, Imports, and Suggests.
Installs OpenCV for use by other packages. OpenCV <https://opencv.org/> is library of programming functions mainly aimed at real-time computer vision. This Lite version installs the stable base version of OpenCV and some of its experimental externally contributed modules. It does not provide R bindings directly.
Fits Relevance Vector Machine (RVM) models for Normal, Epanechnikov, and Bickel prior distributions, and Gaussian or Mexican Hat kernels.
This package provides functions to convert an R colour specification to a colour name. The user can select and create different lists of colour names and different colour metrics for the conversion.
Model based simulation of dynamic networks under tie-oriented (Butts, C., 2008, <doi:10.1111/j.1467-9531.2008.00203.x>) and actor-oriented (Stadtfeld, C., & Block, P., 2017, <doi:10.15195/v4.a14>) relational event models. Supports simulation from a variety of relational event model extensions, including temporal variability in effects, heterogeneity through dyadic latent class relational event models (DLC-REM), random effects, blockmodels, and memory decay in relational event models (Lakdawala, R., 2024 <doi:10.48550/arXiv.2403.19329>). The development of this package was supported by a Vidi Grant (452-17-006) awarded by the Netherlands Organization for Scientific Research (NWO) Grant and an ERC Starting Grant (758791).
This package provides a memory-efficient, visualize-enhanced, parallel-accelerated Genome-Wide Association Study (GWAS) tool. It can (1) effectively process large data, (2) rapidly evaluate population structure, (3) efficiently estimate variance components several algorithms, (4) implement parallel-accelerated association tests of markers three methods, (5) globally efficient design on GWAS process computing, (6) enhance visualization of related information. rMVP contains three models GLM (Alkes Price (2006) <DOI:10.1038/ng1847>), MLM (Jianming Yu (2006) <DOI:10.1038/ng1702>) and FarmCPU (Xiaolei Liu (2016) <doi:10.1371/journal.pgen.1005767>); variance components estimation methods EMMAX (Hyunmin Kang (2008) <DOI:10.1534/genetics.107.080101>;), FaSTLMM (method: Christoph Lippert (2011) <DOI:10.1038/nmeth.1681>, R implementation from GAPIT2': You Tang and Xiaolei Liu (2016) <DOI:10.1371/journal.pone.0107684> and SUPER': Qishan Wang and Feng Tian (2014) <DOI:10.1371/journal.pone.0107684>), and HE regression (Xiang Zhou (2017) <DOI:10.1214/17-AOAS1052>).
Automatic open data acquisition from resources of Polish Head Office of Geodesy and Cartography ('GŠówny UrzÄ d Geodezji i Kartografii') (<https://www.gov.pl/web/gugik>). Available datasets include various types of numeric, raster and vector data, such as orthophotomaps, digital elevation models (digital terrain models, digital surface model, point clouds), state register of borders, spatial databases, geometries of cadastral parcels, 3D models of buildings, and more. It is also possible to geocode addresses or objects using the geocodePL_get() function.
This package provides functions to calculate several ecological indices of individual and population niche width (Araujo's E, clustering and pairwise similarity among individuals, IS, Petraitis W, and Roughgarden's WIC/TNW) to assess individual specialization based on data of resource use. Resource use can be quantified by counts of categories, measures of mass or length, or proportions. Monte Carlo resampling procedures are available for hypothesis testing against multinomial null models. Details are provided in Zaccarelli et al. (2013) <doi:10.1111/2041-210X.12079> and associated references.
This package provides functionality to read settings, statuses and readings of weather stations from the ZENTRA Cloud API <https://zentracloud.com/api/v1/guide#APIGuidelines>.
This package contains miscellaneous functions useful in biostatistics, mostly univariate and multivariate testing procedures with a special emphasis on permutation tests. Many functions intend to simplify user's life by shortening existing procedures or by implementing plotting functions that can be used with as many methods from different packages as possible.
Perform structural reliability analysis, including computation and simulation with system signatures, Samaniego (2007) <doi:10.1007/978-0-387-71797-5>, and survival signatures, Coolen and Coolen-Maturi (2013) <doi:10.1007/978-3-642-30662-4_8>. Additionally supports parametric and topological inference given system lifetime data, Aslett (2012) <https://www.louisaslett.com/PhD_Thesis.pdf>.
This package provides comprehensive methods to measure disclosure risk and data utility for anonymized and synthetic data. Implements attribution-based risk metrics including Correct Attribution Probability (CAP), Targeted CAP (TCAP), Within Equivalence Class Attribution Probability (WEAP), and RAPID (Risk of Attribute Prediction-Induced Disclosure). Also provides distance-based privacy metrics such as Distance to Closest Record (DCR), Nearest Neighbor Distance Ratio (NNDR), and Identical Match Share (IMS). Utility assessment includes propensity score analysis, distribution comparisons, and various statistical tests. Methods are based on Taub et al. (2018) <doi:10.1007/978-3-319-99771-1_9> and related literature. Designed for integration with simPop S4 classes.
This package implements an objective Bayes intrinsic conditional autoregressive prior. This model provides an objective Bayesian approach for modeling spatially correlated areal data using an intrinsic conditional autoregressive prior on a vector of spatial random effects.