Statistical computing
Showing 36 of 40 projects
A powerful Python library for data analysis and manipulation, providing fast, flexible data structures.
A curated list of awesome R packages, frameworks, and software for data science and statistical computing.
A curated list of awesome R packages, frameworks, and software for data science and statistical computing.
A fast and comprehensive machine learning framework for Java, Scala, and Kotlin with state-of-the-art algorithms and data visualization.
A grammar of data manipulation for R, providing a consistent set of verbs to solve common data manipulation challenges.
An integrated development environment (IDE) for the R programming language with a comprehensive workbench and server capabilities.
A comprehensive Rust machine learning framework focused on preprocessing and classical algorithms, akin to scikit-learn.
A comprehensive, dependency-free statistics library for Go with extensive mathematical functions and thorough testing.
A general-purpose literate programming engine for dynamic report generation in R, designed to give users full control over output.
A meta-package for installing and loading core R packages for data science that share common design principles.
A collection of R packages for data science that share common design principles and work together seamlessly.
An R package that converts R functions into web APIs using special code annotations.
An R package for reshaping and tidying data into a consistent format for easier analysis.
A comprehensive Julia package for probability distributions, providing properties, PDFs, sampling, and maximum likelihood estimation.
A fast, modular Bayesian inference library for JAX, providing composable samplers for CPU and GPU.
A modern, object-oriented machine learning framework for R, providing efficient building blocks for ML workflows.
A Vim plugin that enhances editing R scripts by enabling seamless communication between Vim and R.
A fast implementation of random forests for classification, regression, and survival analysis, optimized for high-dimensional data.
A collection of R packages for interacting with Hadoop ecosystems, enabling big data analysis from R.
A curated guide to essential R packages organized by their role in the data science workflow.
A curated collection of free resources to help deepen your understanding of the R programming language.
A JAX-native library of probability distributions and bijectors, reimplementing a subset of TensorFlow Probability with emphasis on readability and extensibility.
A tidy API for graph manipulation in R, providing dplyr verbs and igraph algorithms for network analysis.
An R package for interactive network visualization using the vis.js JavaScript library.
A curated repository of university courses, workshops, and online materials for learning and teaching R programming and data science.
A high-performance MongoDB client for R, built on libmongoc and jsonlite, supporting aggregation, indexing, and streaming.
A Swift library providing probability distributions and statistical functions for probabilistic computing.
A Julia package for implementing and applying Markov chain Monte Carlo (MCMC) methods for Bayesian analysis.
A JAX-based probabilistic programming framework using nested sampling for fast Bayesian inference and evidence computation.
An R package for flexibly rearranging, reshaping, and aggregating data, now superseded by tidyr.
An R package for creating and exporting statistical animations to HTML, GIF, video, and PDF formats.
A C++ library with R interface for practical volume computation and sampling of convex bodies in high dimensions.
A bridge library enabling Clojure to call R functions and use R objects for statistical computing and data science.
An R package providing 2,260 network datasets in igraph format from diverse sources like social networks, animal interactions, and movie co-stars.
An R package that provides a bidirectional interface for calling Julia code from R and mapping objects between both languages.
A convenience meta-package that loads essential Julia packages for statistics with a single import.
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