Sankey and alluvial diagrams visualise flows of quantities across stages in stacked bars. This package makes it easy to create such diagrams using ggplot2'.

Multi-modal magnetic resonance imaging ('MRI') data from the Kirby21 reproducibility study <https://www.nitrc.org/projects/multimodal/>, including functional and structural imaging.

Model-based linear model trees adjusting for spatial correlation using a simultaneous autoregressive spatial lag, Wagner and Zeileis (2019) <doi:10.1111/geer.12146>.

Create R plots visualising ontological terms and the relationships between them with various graphical options - Greene et al. 2017 <doi:10.1093/bioinformatics/btw763>.

This package provides definitions of core classes and methods used by analytic pipelines that query the OMOP (Observational Medical Outcomes Partnership) common data model.

This package provides a user-friendly interface for creating and managing empirical crowd-sourcing studies via API access to <https://www.prolific.co>.

Transcribe audio files using the Speechmatics speech-to-text API <https://www.speechmatics.com/>. Supports custom vocabulary, speaker diarization, punctuation control, and audio filtering.

This package provides an interface to shiny inputs used for filtering vectors, data.frames, and other objects. S7'-based implementation allows for seamless extensibility.

This package provides a graphical user interface to the seasonal package and X-13ARIMA-SEATS', the U.S. Census Bureau's seasonal adjustment software.

This package provides an interactive interface to the tfrmt package. Users can import, modify, and export tables and templates with little to no code.

Access to the C-level R date and datetime code is provided for C-level API use by other packages via registration of native functions. Client packages simply include a single header RApiDatetime.h provided by this package, and also import it. The R Core group is the original author of the code made available with slight modifications by this package.

The rerddapUtils package is an R package that is a set of four main functions designed to work with and extend the rerddap package. These functions includes one for restricting by season, one for splitting large requests, and two for working with projected datasets. There are also two utility functions that provide estimates of the size of a proposed rerddap::griddap() request.

This package contains microarray gene expression data on 57 bladder samples from 5 batches. The data are used as an illustrative example for the sva package.

This package provides an S4 implementation of Eq. (3) and Eq. (7) by David J. Hand and Robert J. Till (2001) <DOI:10.1023/A:1010920819831>.

bake-test automatically discovers how to run local test suites for Ruby projects. It supports rspec, sus, as well as rake.

skiptrace provides a way to access the bindings that relate to exceptions in Ruby, providing more information about the context in which the exception occurred.

This package performs Bayesian t Regression where mean and scale parameters are modeling by lineal regression structures, and the degrees of freedom parameters are estimated.

The bias-corrected estimation methods for the receiver operating characteristics ROC surface and the volume under ROC surfaces (VUS) under missing at random (MAR) assumption.

Collect marketing data from facebook Ads using the Windsor.ai API <https://windsor.ai/api-fields/>. Use four spaces when indenting paragraphs within the Description.

Time parceling method and Bayesian variability modeling methods for modeling within individual variability indicators as predictors.For more details, see <https://github.com/xliu12/IIVpredicitor>.

Testing CRAN and Bioconductor mirror speed by recording download time of src/base/COPYING (for CRAN) and packages/release/bioc/html/ggtree.html (for Bioconductor).

Implementation of Physics-Informed Neural Networks ('PINN') for lifetime estimation under progressive Type-II censoring schemes. Combines parametric baseline hazards with physical differential degradation models.

An interface to explore trends in Twitter data using the Storywrangler Application Programming Interface (API), which can be found here: <https://github.com/janeadams/storywrangler>.

This package provides tools for spatial data analysis. Emphasis on kriging. Provides functions for prediction and simulation. Intended to be relatively straightforward, fast, and flexible.