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).

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>.

Bayesian variable selection, model choice, and regularized estimation for (spatial) generalized additive mixed regression models via stochastic search variable selection with spike-and-slab priors.

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.

This package contains functions for building GenomicState objects from different annotation sources such as Gencode. It also provides access to these files at JHPCE.

This package provides airline on-time data for all flights departing NYC in 2013. It also includes useful metadata on airlines, airports, weather, and planes.

This crate provides various ordering kernels for Apache Arrow arrays. Examples include cmp, ord, partition, rank and sort kernels.

Emacs Refactor (EMR) is a framework for providing language-specific refactoring in Emacs. It includes refactoring commands for a variety of languages, including elisp itself.

This package provides Python bindings to the Rust rpds crate for persistent data structures. It was written initially to support replacing python-pyrsistent.

Examples for Seamless R and C++ integration The Rcpp package contains a C++ library that facilitates the integration of R and C++ in various ways. This package provides some usage examples. Note that the documentation in this package currently does not cover all the features in the package. The site <https://gallery.rcpp.org> regroups a large number of examples for Rcpp'.

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.

Exposes the binary search functions of the C++ standard library (std::lower_bound, std::upper_bound) plus other convenience functions, allowing faster lookups on sorted vectors.

Connect to WFP's Moda platform to R, download data, and obtain the list of individuals with access to the project along with their access level.

Detect events in time-series data. Combines multiple well-known R packages like forecast and neuralnet to deliver an easily configurable tool for multivariate event detection.

This package provides an implementation of the maximum likelihood methods for deriving Elo scores as published in Foerster, Franz et al. (2016) <DOI:10.1038/srep35404>.

Split experiment sentences by different experiment design given by the user and the result can be used in E-prime (<https://pstnet.com/products/e-prime/>).

Collection of functions to enhance ggplot2 and ggiraph'. Provides functions for exploratory plots. All plot can be a static plot or an interactive plot using ggiraph'.

This package provides utilities for Kokudo Suuchi', the GIS data service of the Japanese government. See <https://nlftp.mlit.go.jp/index.html> for more information.

Long Memory Time Series is a collection of functions for estimation, simulation and testing of long memory processes, spurious long memory processes and fractionally cointegrated systems.

This package implements L1 and L2 penalized conditional logistic regression with penalty factors allowing for integration of multiple data sources. Implements stability selection for variable selection.

Includes all the datasets of Sampling: Design and Analysis (3rd edition by Sharon Lohr) in R format and additional functions for analyzing and graphing probability samples.