Statistical Analysis
Showing 36 of 54 projects
Bayesian Modeling and Probabilistic Programming in Python
A command-line tool that provides simple and efficient access to various statistics in git repositories.
A library for probabilistic reasoning and statistical analysis integrated with TensorFlow and JAX.
A Java dataframe and visualization library for data loading, cleaning, transformation, and analysis.
R code examples from the 'Machine Learning for Hackers' book, demonstrating practical machine learning techniques.
An R package for robust anomaly detection in time series and vectors, handling seasonality and trend.
A Python library for automated exploratory data analysis (EDA) with high-density visualizations and target analysis in two lines of code.
An advanced spam filtering system and email processing framework that evaluates messages using regex, statistical analysis, and custom services.
An R package that extends ggplot2 to create publication-ready graphics with statistical details embedded directly in the plots.
Inspects Python source files and provides information about type and location of classes, methods etc
Inspects Python source files and provides information about type and location of classes, methods etc
A PHP benchmarking framework for performance testing, analogous to PHPUnit but for measuring execution time and memory usage.
Python implementation of the Boruta all-relevant feature selection method with scikit-learn compatibility.
A comprehensive Python library for generating and analyzing multi-class confusion matrices with extensive statistical metrics.
The most accurate natural language detection library for Go, excelling with short text and mixed-language content.
Wordlists for statistically likely usernames, optimized for horizontal password attacks and security testing.
A lightweight Python library for anomaly detection and correlation in time series data, enabling root cause analysis.
An open-source Java framework for rapid development of machine learning and statistical applications with large dataset support.
A Java library of stochastic streaming algorithms (sketches) for approximate analysis of massive datasets.
A C++14 library for authoring and executing benchmarks with a GoogleTest-like API, supporting statistical analysis and performance tracking.
A pure Java machine learning library with no external dependencies, offering a wide collection of algorithms and parallel execution support.
An R package for detecting statistically significant breakpoints in time series using robust energy statistics.
An R package that simplifies data import and export by automatically selecting the correct function based on file extension.
Unified ggplot2 interface for visualizing statistical results from popular R packages.
Code and data repository for reproducing examples from 'Evidence-based Software Engineering' book using publicly available data.
Multiple Pairwise Comparisons (Post Hoc) Tests in Python
A header-only C++ micro-benchmarking framework for statistically rigorous performance measurement of small code snippets.
A modular Python framework for exploratory analysis of heterogeneous epidemiological and electronic health record (EHR) data.
R package containing datasets and code examples for the book 'Statistical Analysis of Network Data with R, 2nd Edition'.
A high-performance, large-scale statistical machine learning library written in Common Lisp.
An end-to-end Python outlier detection system with database support, automated machine learning, and unified APIs for statistical, ML, and deep learning models.
A Node.js library for automated Chrome tracing and statistical analysis to benchmark web performance.
An R package with GUI for computational stylistics and authorship attribution through statistical text analysis.
A Python package for automated univariate and bivariate data analysis and visualization to streamline machine learning workflows.
An R package for performing graph theory analyses of brain MRI data from structural, DTI, and resting-state fMRI connectivity.
A .NET library for high-dynamic-range histograms to accurately record and analyze latency and performance measurements.
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