This package provides several layout algorithms to visualize networks which are not part of the igraph library. Most are based on the concept of stress majorization by Gansner et al. (2004) <doi:10.1007/978-3-540-31843-9_25>. Some more specific algorithms emphasize hidden group structures in networks or focus on specific nodes.

This package provides an interface to figshare, a scientific repository to archive and assign DOIs to data, software, figures, and more.

This package provides medium to high level functions for 3D interactive graphics, including functions modelled on base graphics (plot3d(), etc.) as well as functions for constructing representations of geometric objects (cube3d(), etc.). Output may be on screen using OpenGL, or to various standard 3D file formats including WebGL, PLY, OBJ, STL as well as 2D image formats, including PNG, Postscript, SVG, PGF.

This package provides functions to fit kernel density functions to data on temporal activity patterns of animals; estimate coefficients of overlapping of densities for two species; and calculate bootstrap estimates of confidence intervals.

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 a collection of all the estimation functions for spatial cross-sectional models (on lattice/areal data using spatial weights matrices) contained up to now in spdep.

The r-phylogram package is a tool for for developing phylogenetic trees as deeply-nested lists known as "dendrogram" objects. It provides functions for conversion between "dendrogram" and "phylo" class objects, as well as several tools for command-line tree manipulation and import/export via Newick parenthetic text. This improves accessibility to the comprehensive range of object-specific analytical and tree-visualization functions found across a wide array of bioinformatic R packages.

This package provides tools for generating and handling of Universally Unique Identifiers (UUIDs).

This package provides functions for latent class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive Bayes classifier, and more.

This package provides an interface to Amazon Web Services machine learning services, including SageMaker managed machine learning service, natural language processing, speech recognition, translation, and more.

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 easy and simple way to read, write and display bitmap images stored in the PNG format. It can read and write both files and in-memory raw vectors.

This package provides functions for Maximum Likelihood (ML) estimation, non-linear optimization, and related tools. It includes a unified way to call different optimizers, and classes and methods to handle the results from the Maximum Likelihood viewpoint. It also includes a number of convenience tools for testing and developing your own models.

Extracts plain text from Rich Text Format (RTF) file.

This package provides tools for the analysis of complex survey samples. The provided features include: summary statistics, two-sample tests, rank tests, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples; variances by Taylor series linearisation or replicate weights; post-stratification, calibration, and raking; two-phase subsampling designs; graphics; PPS sampling without replacement; principal components, and factor analysis.

This package provides probability mass, distribution, quantile, random-variate generation, and method-of-moments parameter-estimation functions for the Delaporte distribution with parameterization based on Vose (2008). The Delaporte is a discrete probability distribution which can be considered the convolution of a negative binomial distribution with a Poisson distribution. Alternatively, it can be considered a counting distribution with both Poisson and negative binomial components. It has been studied in actuarial science as a frequency distribution which has more variability than the Poisson, but less than the negative binomial.

This package provides drop-in replacements for the base system2() function with fine control and consistent behavior across platforms. It supports clean interruption, timeout, background tasks, and streaming STDIN / STDOUT / STDERR over binary or text connections. The package also provides functions for evaluating expressions inside a temporary fork. Such evaluations have no side effects on the main R process, and support reliable interrupts and timeouts. This provides the basis for a sandboxing mechanism.

This is a package for simplified document database access and manipulation, providing a common API across supported NoSQL databases Elasticsearch, CouchDB, MongoDB as well as SQLite/JSON1, PostgreSQL, and DuckDB.

This package implements Freund and Schapire's Adaboost.M1 algorithm and Breiman's Bagging algorithm using classification trees as individual classifiers. Once these classifiers have been trained, they can be used to predict on new data. Also, cross validation estimation of the error can be done.

This package provides two convenience functions assert() and test_pkg() to facilitate testing R packages.

The ability to tune models is important. tune contains functions and classes to be used in conjunction with other tidymodels packages for finding reasonable values of hyper-parameters in models, pre-processing methods, and post-processing steps.

This package includes tools for marginal maximum likelihood estimation and joint maximum likelihood estimation for unidimensional and multidimensional item response models. The package functionality covers the Rasch model, 2PL model, 3PL model, generalized partial credit model, multi-faceted Rasch model, nominal item response model, structured latent class model, mixture distribution IRT models, and located latent class models. Latent regression models and plausible value imputation are also supported.

This package provides tools for creating and modifying HTTP requests, then performing them and processing the results. httr2 is a re-imagining of httr that uses a pipe-based interface and solves more of the problems that API wrapping packages face.

This package provides a suite of functions for computing various Bayes factors for simple designs, including contingency tables, one- and two-sample designs, one-way designs, general ANOVA designs, and linear regression.