Content-preserving transformations transformations of PDF files such as split, combine, and compress. This package interfaces directly to the qpdf C++ API and does not require any command line utilities. Note that qpdf does not read actual content from PDF files: to extract text and data you need the pdftools package.

This package provides classes and methods for spatial objects that have a registered time column, in particular for irregular spatiotemporal data. The time column can be of any type, but needs to be ordinal. Regularly laid out spatiotemporal data (vector or raster data cubes) are handled by package stars'.

This package provides methods operating on rows and columns of matrices, e.g. rowMedians(), rowRanks(), and rowSds(). There are also some vector-based methods, e.g. binMeans(), madDiff() and weightedMedians(). All methods have been optimized for speed and memory usage.

Ggfittext is a ggplot2 extension for fitting text into boxes.

This package creates a lightweight way to add markdown helpfiles to Shiny apps, using modal dialog boxes, with no need to observe each help button separately.

This package provides other packages with access to the internal R serialization code. Access to this code is provided at the C function level by using the registration of native function mechanism. Client packages simply include a single header file RApiSerializeAPI.h provided by this package.

This package provides some very simple method functions for confidence interval calculation and to distill pertinent information from a potentially complex object; primarily used in common with the packages extRemes and SpatialVx.

Functions implemented in this package allow coercing (i.e. convert) network data between classes provided by other R packages. Currently supported classes are those defined in packages network and igraph.

This package provides an implementation of the Harmony algorithm for single cell integration. This package includes a standalone Harmony function and interfaces to external frameworks.

This package provides a minimal R and C++ API for parsing well-known binary and well-known text representation of geometries to and from R-native formats. Well-known binary is compact and fast to parse; well-known text is human-readable and is useful for writing tests. These formats are only useful in R if the information they contain can be accessed in R, for which high-performance functions are provided here.

This package provides flexible parametric models for time-to-event data, including the Royston-Parmar spline model, generalized gamma and generalized F distributions. Any user-defined parametric distribution can be fitted, given at least an R function defining the probability density or hazard. There are also tools for fitting and predicting from fully parametric multi-state models.

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.

This package improves the user experience of Shiny apps by helping to provide feedback when required inputs are missing, or input values are not valid.

This R package provides a single procedure guix.install(), which allows users to install R packages via Guix right from within their running R session. If the requested R package does not exist in Guix at this time, the package and all its missing dependencies will be imported recursively and the generated package definitions will be written to ~/.Rguix/packages.scm. This record of imported packages can be used later to reproduce the environment, and to add the packages in question to a proper Guix channel (or Guix itself). guix.install() not only supports installing packages from CRAN, but also from Bioconductor or even arbitrary git or mercurial repositories, replacing the need for installation via devtools.

Finding an optimal Bayesian experimental design involves maximizing an objective function given by the expectation of some appropriately chosen utility function with respect to the joint distribution of unknown quantities (including responses). This objective function is usually not available in closed form and the design space can be continuous and of high dimensionality. This package uses Approximate Coordinate Exchange (ACE) to maximise an approximation to the expectation of the utility function.

This package creates dummy columns from columns that have categorical variables (character or factor types). You can also specify which columns to make dummies out of, or which columns to ignore. Also creates dummy rows from character, factor, and Date columns. This package provides a significant speed increase from creating dummy variables through model.matrix().

This package is a toolkit for working with Bezier curves and splines. The package provides functions for point generation, arc length estimation, degree elevation and curve fitting.

This package provides well-known outlier detection techniques in the univariate case. Methods to deal with skewed distribution are included too. The Hidiroglou-Berthelot (1986) method to search for outliers in ratios of historical data is implemented as well. When available, survey weights can be used in outliers detection.

This package provides data structures and algorithms for k-ary relations with arbitrary domains, featuring relational algebra, predicate functions, and fitters for consensus relations.

This package provides helper functions with a consistent interface to coerce and verify the types and shapes of values for input checking.

This package provides functionality to assert conditions that have to be met so that errors in data used in analysis pipelines can fail quickly. It is similar to stopifnot() but more powerful, friendly, and easier for use in pipelines.

The ACE file format is used in genomics to store contigs from sequencing machines. This tools converts it into FASTQ format. Both formats contain the sequence characters and their corresponding quality information. Unlike the FASTQ file, the ACE file stores the quality values numerically. The conversion algorithm uses the standard Sanger formula. The package facilitates insertion into pipelines, and content inspection.

This package provides a number of methods for creating and augmenting Latin Hypercube Samples.

This package computes the areas under the precision-recall (PR) and ROC curve for weighted (e.g. soft-labeled) and unweighted data. In contrast to other implementations, the interpolation between points of the PR curve is done by a non-linear piecewise function. In addition to the areas under the curves, the curves themselves can also be computed and plotted by a specific S3-method.