This package implements the following methods for event history analysis: Risk regression models for survival endpoints also in the presence of competing risks are fitted using binomial regression based on a time sequence of binary event status variables. A formula interface for the Fine-Gray regression model and an interface for the combination of cause-specific Cox regression models. A toolbox for assessing and comparing performance of risk predictions (risk markers and risk prediction models). Prediction performance is measured by the Brier score and the area under the ROC curve for binary possibly time-dependent outcome. Inverse probability of censoring weighting and pseudo values are used to deal with right censored data. Lists of risk markers and lists of risk models are assessed simultaneously. Cross-validation repeatedly splits the data, trains the risk prediction models on one part of each split and then summarizes and compares the performance across splits.

This package provides a low-level interface to the Java VM very much like .C/.Call and friends. It allows the creation of objects, calling methods and accessing fields.

This package provides functions to make useful (and pretty) plots for scientific plotting. Additional plotting features are added for base plotting, with particular emphasis on making attractive log axis plots.

This package provides procedures to answer the following questions: How much ram do you need to store a 100,000 by 100,000 matrix? How much ram is your current R session using? How much ram do you even have?

This package provides an optimization method based on sequential quadratic programming for maximum likelihood estimation of the mixture proportions in a finite mixture model where the component densities are known. The algorithm is expected to obtain solutions that are at least as accurate as the state-of-the-art MOSEK interior-point solver, and they are expected to arrive at solutions more quickly when the number of samples is large and the number of mixture components is not too large.

This package provides a developer-facing interface to Arrow Database Connectivity (ADBC) for the purposes of driver development, driver testing, and building high-level database interfaces for users. ADBC is an API standard for database access libraries that uses Arrow for result sets and query parameters.

This package provides all final tables of Germany's highest football league, the Bundesliga. It contains data from 1964 to 2016.

This package provides string and binary representations of objects for several formats and MIME types.

This package provides functionality to create pretty word clouds, visualize differences and similarity between documents, and avoid over-plotting in scatter plots with text.

The package includes the necessary functions to construct a self-organizing map of data, to evaluate the statistical significance of the observed data patterns, and to visualize the results.

This package fits models for genotypic disequilibria, as described in Huttley and Wilson (2000), Weir (1996) and Weir and Wilson (1986). Contrast terms are available that account for first order interactions between loci. It also implements, for a single locus in a single population, a conditional exact test for Hardy-Weinberg equilibrium.

This package provides an interface to the rich display capabilities of Jupyter front-ends (e.g. Jupyter Notebook). It is designed to be used from a running IRkernel session.

This package provides tools to obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. It can be used to compute contrasts or linear functions of EMMs, trends, and comparisons of slopes.

This package provides lots of plotting, various labeling, axis and color scaling functions for R.

Annoy is a small C++ library for Approximate Nearest Neighbors written for efficient memory usage as well an ability to load from and save to disk. This package provides an R interface.

This package provides tools to identify and read BMP, JPEG, PNG, and TIFF format bitmap images. Identification defaults to the use of the magic number embedded in the file rather than the file extension.

This package provides a fast and improved implementation of the graphical LASSO.

This package enhances the R Optimization Infrastructure (ROI) package by registering the GLPK solver. It allows for solving mixed integer linear programming (MILP) problems as well as all variants/combinations of LP and IP.

The Datasaurus Dozen is a set of datasets with the same summary statistics. They retain the same summary statistics despite having radically different distributions. The datasets represent a larger and quirkier object lesson that is typically taught via Anscombe's Quartet (available in the 'datasets' package). Anscombe's Quartet contains four very different distributions with the same summary statistics and as such highlights the value of visualisation in understanding data, over and above summary statistics. As well as being an engaging variant on the Quartet, the data is generated in a novel way. The simulated annealing process used to derive datasets from the original Datasaurus is detailed in "Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing" doi:10.1145/3025453.3025912.

This package lets you fit pedigree-based mixed-effects models.

This package provides the means to compile user-supplied C++ functions with Rcpp and retrieve an XPtr that can be passed to other C++ components.

This package provides an interface to Amazon Web Services analytics services, including Elastic MapReduce Hadoop and Spark big data service, Elasticsearch search engine, and more.

This package provides a fully DBI-compliant Rcpp-backed interface to PostgreSQL, a relational database.

This package provides a re-implementation of the gWidgets API. The API is defined in this package. A second, toolkit-specific package is required to use it.