This package provides tools for fitting possibly high dimensional penalized regression models. The penalty structure can be any combination of an L1 penalty (lasso and fused lasso), an L2 penalty (ridge) and a positivity constraint on the regression coefficients. The supported regression models are linear, logistic and Poisson regression and the Cox Proportional Hazards model. Cross-validation routines allow optimization of the tuning parameters.

This package provides functions for reading, writing, plotting, and manipulating phylogenetic trees, analyses of comparative data in a phylogenetic framework, ancestral character analyses, analyses of diversification and macroevolution, computing distances from DNA sequences, and several other tools.

This is a subset of the original spatstat package, containing the user-level code from spatstat which performs geometrical operations, except for the geometry of linear networks.

In order to smoothly animate the transformation of polygons and paths, many aspects needs to be taken into account, such as differing number of control points, changing center of rotation, etc. The transformr package provides an extensive framework for manipulating the shapes of polygons and paths and can be seen as the spatial brother to the tweenr package.

This package provides tools to convert plot function calls (using expression or formula) to grob or ggplot objects that are compatible with the grid and ggplot2 environment. With this package, we are able to e.g. use cowplot to align plots produced by base graphics, grid, lattice, vcd etc. by converting them to ggplot objects.

Logging functions in RcppSpdlog provide access to the logging functionality from the spdlog C++ library. This package offers shorter convenience wrappers for the R functions which match the C++ functions, namely via, say, spdl::debug() at the debug level. The actual formatting is done by the fmt::format() function from the fmtlib library (that is also std::format() in C++20 or later).

This package provides tools to export R data as LaTeX and HTML tables.

This package implements time series clustering along with optimized techniques related to the dynamic time warping distance and its corresponding lower bounds. The implementations of partitional, hierarchical, fuzzy, k-Shape and TADPole clustering are available. Functionality can be easily extended with custom distance measures and centroid definitions. Implementations of DTW barycenter averaging, a distance based on global alignment kernels, and the soft-DTW distance and centroid routines are also provided. All included distance functions have custom loops optimized for the calculation of cross-distance matrices, including parallelization support. Several cluster validity indices are included.

This package provides tools to get text from images of text using Abbyy Cloud Optical Character Recognition (OCR) API. With abbyyyR, one can easily OCR images, barcodes, forms, documents with machine readable zones, e.g. passports and get the results in a variety of formats including plain text and XML. To learn more about the Abbyy OCR API, see http://ocrsdk.com/.

This package provides means to run simulations for adaptive seamless designs with and without early outcomes for treatment selection and subpopulation type designs.

This package provides a collection of functions helpful in learning the basic tenets of Bayesian statistical inference. It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions. It contains MCMC algorithms for summarizing posterior distributions defined by the user. It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.

How fast can you type R functions on your keyboard? Find out by running a zty.pe game: export R functions as instructions to type to destroy opponents' vessels.

The wordspace package turns R into an interactive laboratory for empirical research on distributional semantic models (DSM). It consists of a small set of carefully designed functions, most of which

• encapsulate non-trivial R operations in a user-friendly manner or

• provide efficient and memory-lean C implementations of key operations.

Recipes is an extensible framework to create and preprocess design matrices. Recipes consist of one or more data manipulation and analysis "steps". Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting design matrices can then be used as inputs into statistical or machine learning models.

This is a pure R implementation of the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) with optional restarts (IPOP-CMA-ES).

The pls package implements multivariate regression methods: Partial Least Squares Regression (PLSR), Principal Component Regression (PCR), and Canonical Powered Partial Least Squares (CPPLS). It supports:

• several algorithms: the traditional orthogonal scores (NIPALS) PLS algorithm, kernel PLS, wide kernel PLS, Simpls, and PCR through svd

• multi-response models (or PLS2)

• flexible cross-validation

• Jackknife variance estimates of regression coefficients

• extensive and flexible plots: scores, loadings, predictions, coefficients, (R)MSEP, R², and correlation loadings

• formula interface, modelled after lm(), with methods for predict, print, summary, plot, update, etc.

• extraction functions for coefficients, scores, and loadings

• MSEP, RMSEP, and R² estimates

• multiplicative scatter correction (MSC)

This package provides an implementation of maximum likelihood estimators for a variety of heavy tailed distributions, including both the discrete and continuous power law distributions. Additionally, a goodness-of-fit based approach is used to estimate the lower cut-off for the scaling region.

This package provides simple, flexible assertions on data.frame or data.table objects with verbose output for vetting. While other assertion packages apply towards more general use-cases, assertable is tailored towards tabular data. It includes functions to check variable names and values, whether the dataset contains all combinations of a given set of unique identifiers, and whether it is a certain length. In addition, assertable includes utility functions to check the existence of target files and to efficiently import multiple tabular data files into one data.table.

The GNU Scientific Library (or GSL) is a collection of numerical routines for scientific computing. It is particularly useful for C and C++ programs as it provides a standard C interface to a wide range of mathematical routines. There are over 1000 functions in total with an extensive test suite. The RcppGSL package provides an easy-to-use interface between GSL data structures and R using concepts from Rcpp which is itself a package that eases the interfaces between R and C++.

The googleVis package provides an interface between R and the Google Charts API. Google Charts offer interactive charts which can be embedded into web pages. The functions of the googleVis package allow the user to visualise data stored in R data frames with Google Charts without uploading the data to Google. The output of a googleVis function is HTML code that contains the data and references to JavaScript functions hosted by Google. googleVis makes use of the internal R HTTP server to display the output locally.

int64 values can be created and accessed via the bit64 package and its integer64 class which package the int64 representation cleverly into a double. The nanotime package builds on this to support nanosecond-resolution timestamps. This package helps conversions between R and C++ via several helper functions provided via a single header file. A complete example client package is included as an illustration.

This package contains some functions to help users (especially data explorers) to make more sense of their variables and take the most out of variables and hardware resources. Functions in this package are supposed to be efficient and easy to use.

This package exposes R bindings to jsTree, a JavaScript library that supports interactive trees, to enable rich, editable trees in Shiny.

This is a deprecated package for accessing huge amounts of data. Cross-platform alternatives are the following packages: bigmemory (CRAN), ff (CRAN), or BufferedMatrix (Bioconductor). The main usage of it was inside the aroma.affymetrix package.