The package is a part of the gDR suite. It helps to prepare raw drug response data for downstream processing. It mainly contains helper functions for importing/loading/validating dose-response data provided in different file formats.

This package provides the infrastructure for association rule-based classification including the algorithms CBA, CMAR, CPAR, C4.5, FOIL, PART, PRM, RCAR, and RIPPER to build associative classifiers. Hahsler et al (2019) <doi:10.32614/RJ-2019-048>.

This package provides numerous utilities for acquiring and analyzing baseball data from online sources such as Baseball Reference <https://www.baseball-reference.com/>, FanGraphs <https://www.fangraphs.com/>, and the MLB Stats API <https://www.mlb.com/>.

Extends blockr.core with interactive blocks for reading and writing data files. Supports CSV, Excel, Parquet, RDS, and other formats through a graphical interface without writing code directly. Includes file browser integration and configurable import/export options.

This package creates ggplot2 Cumulative Residual (CURE) plots to check the goodness-of-fit of a count model; or the tables to create a customized version. A dataset of crashes in Washington state is available for illustrative purposes.

Many functions to easily vizualise and estimate indicators such as proportions, means, medians and continuous/discrete distributions from complex survey data. The package also estimates confidence intervals for all indicators, compares different groups and computes different statistical tests.

Implementation of the FVIBES, the Fuzzy Variable-Importance Based Eigenspace Separation algorithm as described in the paper by Ghashti, J.S., Hare, W., and J.R.J. Thompson (2025). Variable-Weighted Adjacency Constructions for Fuzzy Spectral Clustering. Submitted.

Define and compute with generalized spherical distributions - multivariate probability laws that are specified by a star shaped contour (directional behavior) and a radial component. The methods are described in Nolan (2016) <doi:10.1186/s40488-016-0053-0>.

This package provides tools to measure the reliability of an Information Retrieval test collection. It allows users to estimate reliability using Generalizability Theory and map those estimates onto well-known indicators such as Kendall tau correlation or sensitivity.

One can find single-stage and two-stage designs for a phase II single-arm study with either efficacy or safety/toxicity endpoints as described in Kim and Wong (2019) <doi:10.29220/CSAM.2019.26.2.163>.

This package contains basic tools for sample size estimation in studies of interobserver/interrater agreement (reliability). Includes functions for both the power-based and confidence interval-based methods, with binary or multinomial outcomes and two through six raters.

This package provides easy access for sentiment lexicons for those who want to do text analysis in Portuguese texts. As of now, two Portuguese lexicons are available: SentiLex-PT02 and OpLexicon (v2.1 and v3.0).

Perform sensitivity analysis on ordinary differential equation based models, including ad-hoc graphical analyses based on structured sequences of parameters as well as local sensitivity analysis. Functions are provided for creating inputs, simulating scenarios and plotting outputs.

An enterprise-targeted scalable and UI-standardized shiny framework including a variety of developer convenience functions with the goal of both streamlining robust application development while assisting with creating a consistent user experience regardless of application or developer.

Sensitivity and power analysis, for calculating statistics describing pedigrees from wild populations, and for visualizing pedigrees. This is a reboot of the methods developed by Morrissey and Wilson (2010) <doi: 10.1111/j.1755-0998.2009.02817.x>.

This package provides tools for constructing detailed synthetic human populations from frequency tables. Add ages based on age groups and sex, create households, add students to education facilities, create employers, add employers to employees, and create interpersonal networks.

The sparse vector field consensus (SparseVFC) algorithm (Ma et al., 2013 <doi:10.1016/j.patcog.2013.05.017>) for robust vector field learning. Largely translated from the Matlab functions in <https://github.com/jiayi-ma/VFC>.

This package provides a mechanism for easily generating and organizing a collection of seeds from a single seed, which may be subsequently used to ensure reproducibility in processes/pipelines that utilize multiple random components (e.g., trial simulation).

Compute the values of various parameters evaluating how similar two multidimensional datasets structures are in multidimensional space, as described in: Jouan-Rimbaud, D., Massart, D. L., Saby, C. A., Puel, C. (1998), <doi:10.1016/S0169-7439(98)00005-7>. The computed parameters evaluate three properties, namely, the direction of the data sets, the variance-covariance of the data points, and the location of the data sets centroids. The package contains workhorse function jrparams(), as well as two helper functions Mboxtest() and JRsMahaldist(), and four example data sets.

We implement linear regression when the outcome of interest and some of the covariates are observed in two different datasets that cannot be linked, based on D'Haultfoeuille, Gaillac, Maurel (2022) <doi:10.3386/w29953>. The package allows for common regressors observed in both datasets, and for various shape constraints on the effect of covariates on the outcome of interest. It also provides the tools to perform a test of point identification. See the associated vignette <https://github.com/cgaillac/RegCombin/blob/master/RegCombin_vignette.pdf> for theory and code examples.

This package provides generic functions for interacting with the AnVIL system. Packages that use either GCP or Azure in AnVIL are built on top of AnVILBase. Extension packages will provide methods for interacting with other cloud providers.

Cyclomatic complexity is a software metric, used to indicate the complexity of a program. It is a quantitative measure of the number of linearly independent paths through a program's source code. This package provides tools to compute this metric.

The tidyverse is a set of packages that work in harmony because they share common data representations and API design. This package is designed to make it easy to install and load multiple tidyverse packages in a single step.

This package provides an extension of the functionality of the Matrix package for using sparse matrices. Some of the functions are very general, while other are highly specific for the special data format used for quantitative language comparison (QLC).