The r-nleqslv package solves a system of nonlinear equations using a Broyden or a Newton method with a choice of global strategies such as line search and trust region. There are options for using a numerical or user supplied Jacobian, for specifying a banded numerical Jacobian and for allowing a singular or ill-conditioned Jacobian.

The purpose of this package is to provide a lightweight and unified Future API for sequential and parallel processing of R expression via futures. This package implements sequential, multicore, multisession, and cluster futures. With these, R expressions can be evaluated on the local machine, in parallel a set of local machines, or distributed on a mix of local and remote machines. Extensions to this package implement additional backends for processing futures via compute cluster schedulers etc. Because of its unified API, there is no need to modify any code in order to switch from sequential on the local machine to, say, distributed processing on a remote compute cluster.

This package provides a parallel backend for the %dopar% function using the parallel package.

This is a package for estimation of one-dimensional probability distributions including kernel density estimation, weighted empirical cumulative distribution functions, Kaplan-Meier and reduced-sample estimators for right-censored data, heat kernels, kernel properties, quantiles and integration.

This package estimates optimal cutpoints for binary classification metrics. It also validates performance using bootstrapping. Some methods for more robust cutpoint estimation are supported, e.g. a parametric method assuming normal distributions, bootstrapped cutpoints, and smoothing of the metric values per cutpoint using Generalized Additive Models. Various plotting functions are included.

This is a package for variable elimination (Gaussian elimination, Fourier-Motzkin elimination), Moore-Penrose pseudoinverse, reduction to reduced row echelon form, value substitution, projecting a vector on the convex polytope described by a system of (in)equations, simplify systems by removing spurious columns and rows and collapse implied equalities, test if a matrix is totally unimodular, compute variable ranges implied by linear (in)equalities.

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.

This package provides beanplots, an alternative to boxplot/stripchart/violin plots. It can be used to plot univariate comparison graphs.

This package provides a collection of functions to compute the standardized effect sizes for experiments (Cohen d, Hedges g, Cliff delta, Vargha-Delaney A). The computation algorithms have been optimized to allow efficient computation even with very large data sets.

This is package for regression modeling using rules with added instance-based corrections.

This package provides tools for HTML generation and output in R.

This package provides a simple yet powerful logging utility. Based loosely on log4j, futile.logger takes advantage of R idioms to make logging a convenient and easy to use replacement for cat and print statements.

This package reads and writes data files like CSV, TSV and FWF. When reading it uses a quick initial indexing step, then reads the values lazily, so only the data you actually use needs to be read. The writer formats the data in parallel and writes to disk asynchronously from formatting.

This package provides implementations of the SHA-3 cryptographic hash and SHAKE256 extendable-output functions (XOF).

R's default conflict management system gives the most recently loaded package precedence. This can make it hard to detect conflicts, particularly when they arise because a package update creates ambiguity that did not previously exist. The conflicted package takes a different approach, making every conflict an error and forcing you to choose which function to use.

This package provides a toolkit with infrastructure for representing, summarizing, and visualizing tree-structured regression and classification models.

Solving a system of linear equations is one of the most fundamental computational problems for many fields of mathematical studies, such as regression problems from statistics or numerical partial differential equations. This package provides basic stationary iterative solvers such as Jacobi, Gauss-Seidel, Successive Over-Relaxation and SSOR methods. Nonstationary, also known as Krylov subspace methods are also provided. Sparse matrix computation is also supported in that solving large and sparse linear systems can be manageable using the Matrix package along with RcppArmadillo.

This package aims to provide the most useful subset of Boost libraries for template use among CRAN packages.

This package implements functionality for exploratory data analysis and nonparametric analysis of spatial data, mainly spatial point patterns, in the spatstat family of packages. Methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported.

This package lets you generate random colors, possibly with a given hue or a given luminosity.

The package converts the input in any one of character, integer, numeric, factor, or an ordered type into POSIXct (or Date) objects, using one of a number of predefined formats, and relying on Boost facilities for date and time parsing.

This package provides a system for querying, retrieving and analyzing protocol- and results-related information on clinical trials from three public registers, the European Union Clinical Trials Register (EUCTR), ClinicalTrials.gov (CTGOV) and the ISRCTN. Trial information is downloaded, converted and stored in a database. Functions are included to identify deduplicated records, to easily find and extract variables (fields) of interest even from complex nesting as used by the registers, and to update previous queries. The package can be used for meta-analysis and trend-analysis of the design and conduct as well as for results of clinical trials.

This package provides a set of R functions for identifying and correcting HGNC human gene symbols. In addition, you can identify MGI mouse gene symbols, which have been converted to date format by Excel, withdrawn, or aliased. It also contains functions for reversibly converting between HGNC symbols and valid R names.

OpenTelemetry is a collection of tools, APIs, and SDKs used to instrument, generate, collect, and export telemetry data (metrics, logs, and traces) for analysis in order to understand your software's performance and behavior. This package implements the OpenTelemetry API. Use this package as a dependency if you want to instrument your R package for OpenTelemetry.