This package provides comorbidity classification algorithms such as the Pediatric Complex Chronic Conditions (PCCC), Charlson, and Elixhauser indices, supports longitudinal comorbidity flagging across encounters, and includes utilities for working with medical coding schemas such as the International Classification of Diseases (ICD).

High-throughput, flexible and reproducible extraction of data from figures in primary research papers. metaDigitise() can extract data and / or automatically calculate summary statistics for users from box plots, bar plots (e.g., mean and errors), scatter plots and histograms.

This package provides tools for traversing and working with National Hydrography Dataset Plus (NHDPlus) data. All methods implemented in nhdplusTools are available in the NHDPlus documentation available from the US Environmental Protection Agency <https://www.epa.gov/waterdata/basic-information>.

Install and control Open Source Routing Machine ('OSRM') backend executables to prepare routing data and run/stop a local OSRM server. For computations with the running server use the osrm package for R (<https://cran.r-project.org/package=osrm>).

This package provides a function for fitting various penalized Bayesian cumulative link ordinal response models when the number of parameters exceeds the sample size. These models have been described in Zhang and Archer (2021) <doi:10.1186/s12859-021-04432-w>.

This package implements piecewise structural equation modeling from a single list of structural equations, with new methods for non-linear, latent, and composite variables, standardized coefficients, query-based prediction and indirect effects. See <http://jslefche.github.io/piecewiseSEM/> for more.

This package provides the output of running various transcript abundance quantifiers on a set of 6 RNA-seq samples from the GEUVADIS project. The quantifiers were Cufflinks, RSEM, kallisto, Salmon and Sailfish. Alevin example output is also included.

Appraisal integrates with bundler and rake to test your library against different versions of dependencies in repeatable scenarios called "appraisals." Appraisal is designed to make it easy to check for regressions in your library without interfering with day-to-day development using Bundler.

Test::Unit is unit testing framework for Ruby, based on xUnit principles. These were originally designed by Kent Beck, creator of extreme programming software development methodology, for Smalltalk's SUnit. It allows writing tests, checking results and automated testing in Ruby.

An experiment data package associated with the publication Dona et al. (2013). Package contains runnable vignettes showing an example image segmentation for one posterior lateral line primordium, and also the data table and code used to analyze tissue-scale lifetime-ratio statistics.

This package provides functions to prepare and filter an origin-destination matrix for thematic flow mapping purposes. This comes after Bahoken, Francoise (2016), Mapping flow matrix a contribution, PhD in Geography - Territorial sciences. See Bahoken (2017) <doi:10.4000/netcom.2565>.

This package provides tools for working with observational health data in the Observational Medical Outcomes Partnership (OMOP) Common Data Model format with a pipe friendly syntax. Common data model database table references are stored in a single compound object along with metadata.

Allows you to connect to data sources across the crypto ecosystem. This data can enable a range of activity such as portfolio tracking, programmatic trading, or industry analysis. The package is described in French (2024) <https://github.com/TrevorFrench/cryptotrackr/wiki>.

Extends the mlr3 package and ecosystem to time series forecasting. Provides forecasting tasks, learners, resampling strategies, performance measures, and mlr3pipelines operators for time-series feature engineering. Machine learning regression learners can be turned into forecasters through recursive and direct multi-step strategies.

The Dirichlet (aka NBD-Dirichlet) model describes the purchase incidence and brand choice of consumer products. We estimate the model and summarize various theoretical quantities of interest to marketing researchers. Also provides functions for making tables that compare observed and theoretical statistics.

This package implements a semiparametric estimator for the odds ratio model with censored, time-lagged, ordered categorical outcome in a randomized clinical trial that incorporates baseline and time-dependent information. Tsiatis AA, Davidian M, Holloway ST (2023) <doi:10.1111/biom.13603>.

This package provides a versatile range of functions, including exploratory data analysis, time-series analysis, organizational network analysis, and data validation, whilst at the same time implements a set of best practices in analyzing and visualizing data specific to Microsoft Viva Insights'.

This package performs two-sample comparisons using the restricted mean survival time (RMST) when survival curves end at different time points between groups. This package implements a sensitivity approach that allows the threshold timepoint tau to be specified after the longest survival time in the shorter survival group. Two kinds of between-group contrast estimators (the difference in RMST and the ratio of RMST) are computed: Uno et al(2014)<doi:10.1200/JCO.2014.55.2208>, Uno et al(2022)<https://CRAN.R-project.org/package=survRM2>, Ueno and Morita(2023)<doi:10.1007/s43441-022-00484-z>.

This package lets you fit generalized linear mixed models for a single grouping factor under maximum likelihood approximating the integrals over the random effects with an adaptive Gaussian quadrature rule; Jose C. Pinheiro and Douglas M. Bates (1995) <doi:10.1080/10618600.1995.10474663>.

This package provides a complete ROCm toolchain for C/C++ development to be installed in user profiles. This includes Clang, as well as libc (headers and binaries, plus debugging symbols in the debug output), Binutils, the ROCm device libraries, and the ROCr runtime.

The ChromHeatMap package can be used to plot genome-wide data (e.g. expression, CGH, SNP) along each strand of a given chromosome as a heat map. The generated heat map can be used to interactively identify probes and genes of interest.

Frequentist statistical inference for cluster randomised trials with multiple outcomes that controls the family-wise error rate and provides nominal coverage of confidence sets. A full description of the methods can be found in Watson et al. (2023) <doi:10.1002/sim.9831>.

This package contains functions that check for formatting of the Subject Phenotype data set and data dictionary as specified by the National Center for Biotechnology Information (NCBI) Database of Genotypes and Phenotypes (dbGaP) <https://www.ncbi.nlm.nih.gov/gap/docs/submissionguide/>.

Validates data frames against a defined schema. Produces a report of the checks performed and any issues found, with index and entry value where appropriate. Backend checks are performed using pointblank Richard Iannone et al (2025) <doi:10.32614/CRAN.package.pointblank>.