Search Results for "statistical"
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Showing 30 open source projects for "statistical"
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Orange Data Mining
Orange: Interactive data analysis
Open source machine learning and data visualization. Build data analysis workflows visually, with a large, diverse toolbox. Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections. Interactive data exploration for rapid qualitative analysis with clean visualizations. ... -
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awesome-single-cell
Community-curated list of software packages and data resources
...Rapid, accurate and memory-frugal preprocessing of single-cell and single-nucleus RNA-seq data. Find bimodal, unimodal, and multimodal features in your data. Ascend is an R package comprised of fast, streamlined analysis functions optimized to address the statistical challenges of single cell RNA-seq. The package incorporates novel and established methods to provide a flexible framework to perform filtering, quality control, normalization, dimension reduction, clustering, differential expression and a wide-range of plotting. An analytical framework for big-scale single cell data. Transform percentage-based units into a 2d space to evaluate changes in distribution with both magnitude and direction. -
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Gwyddion
Scanning probe microscopy data visualisation and analysis
A data visualization and processing tool for scanning probe microscopy (SPM, i.e. AFM, STM, MFM, SNOM/NSOM, ...) and profilometry data, useful also for general image and 2D data analysis. -
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sadsa
SADSA (Software Application for Data Science and Analytics)
SADSA (Software Application for Data Science and Analytics) is a Python-based desktop application designed to simplify statistical analysis, machine learning, and data visualization for students, researchers, and data professionals. Built using Python for the GUI, SADSA provides a menu-driven interface for handling datasets, applying transformations, running advanced statistical tests, machine learning algorithms, and generating insightful plots — all without writing code. -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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FreeSEM
Free and open-source desktop application designed for SEM
FreeSEM is a free, open-source desktop application designed for researchers and students to perform Structural Equation Modeling (SEM) for statistical and research analysis. It allows users to visually build models using a drag-and-drop interface to create path diagrams and analyze relationships between observed and latent variables. The software supports methods such as exploratory factor analysis, covariance-based SEM, partial least squares SEM, and meta-SEM, and it provides model fit statistics like CFI, TLI, RMSEA, SRMR, and chi-square to evaluate models. ... -
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Uranie
Uranie is CEA's uncertainty analysis platform, based on ROOT
Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is available both for Unix and Windows platforms (a dedicated platform archive is available on request). Note : if you have downloaded version 3.12 before the 8th of february, a patch exists for a minor bug on TOutputFileKey file, don't hesitate to ask us. -
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Data Preprocessing Automate
Data Preprocessing Automation: A GUI for easy data cleaning & visualiz
Data Preprocessing Automation is a Python-based GUI application designed to simplify and automate data preprocessing tasks. It allows users to upload Excel files, automatically handle missing values, remove duplicates, and detect and remove outliers using statistical methods. The application provides data visualization tools, including box plots for distribution analysis and scatter plots for exploring relationships between variables. Users can download the processed data for further analysis. Built with Tkinter, Pandas, Matplotlib, and Seaborn, it ensures an intuitive interface and efficient performance. ... -
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Parallel and Distributed Process System
OmniSim simulates parallel and distributed processing systems
Parallel and Distributed Process OmniSim Computational Neuroscience: Large-scale neural population dynamics, brain-inspired computing architectures, and neuro-symbolic AI systems 🧬 Scientific Overview PDP-OmniSim is an advanced computational framework for simulating parallel and distributed processing systems, with cutting-edge applications in computational neuroscience, distributed computing, and complex systems modeling. The framework provides researchers with robust tools for... -
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DataMelt
Computation and Visualization environment
...This Java multiplatform program is integrated with several scripting languages such as Jython (Python), Groovy, JRuby, BeanShell. DMelt can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential equations. Linear, non-linear and symbolic regression are also available. Neural networks and various data-manipulation methods are integrated using powerful Java API. Elements of symbolic computations using Octave/Matlab scripting are supported. -
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AlphaPlot
Interactive scientific graphing and data analysis software.
Alpha Plot can generate different types of 2D and 3D plots (such as line, scatter, bar, pie, and surface plots) from data that is either imported from ASCII files, entered by hand, or calculated using formulas. The data is held in spreadsheets which are referred to as tables with column-based data (typically X and Y values for 2D plots) or matrices (for 3D plots). The spreadsheets as well as graphs and note windows are gathered in a project and can be organized using folders. The built-in... -
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Reproducible-research
A Reproducible Data Analysis Workflow with R Markdown, Git, Make, etc.
...It combines the benefits of various open-source software tools including R Markdown, Git, Make, and Docker, whose interplay ensures seamless integration of version management, dynamic report generation conforming to various journal styles, and full cross-platform and long-term computational reproducibility. The workflow ensures meeting the primary goals that 1) the reporting of statistical results is consistent with the actual statistical results (dynamic report generation), 2) the analysis exactly reproduces at a later point in time even if the computing platform or software is changed (computational reproducibility), and 3) changes at any time (during development and post-publication) are tracked, tagged, and documented while earlier versions of both data and code remain accessible. -
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ETL, data warehousing, data mining, OLAP, business intelligence (BI) in Java. 500+ modules: extract, transform, load (ETL), data mining, data analysis + Weka, statistical forecasting, preprocessing, validation, visualization, OLAP, business intelligence.
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QtiPlot is a user-friendly, platform independent data analysis and visualization application similar to the non-free Windows program Origin.
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GAPE
proteogenomic analysis software
...This software allows concurrent querying of proteomic and genomic databases to refining the genome and proteome annotations comprehensively. This includes MS data and database construction, database searches, FDR calculations, statistical result integration, validation of annotated genes, identification of previously unidentified genes, protein level identification of alternative spliced variants and SAAV, biological interpretation, and global PTM discovery. -
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DSTK - DataScience ToolKit
DSTK - DataScience ToolKit for All of Us
DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. -
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Epidat
Statistical data analysis
Programa multiplataforma de libre distribución para el análisis estadístico y epidemiológico de datos. Free distribution cross-platform program for statistical and epidemiological analysis of data. Sitio web: http://www.sergas.es/Saude-publica/EPIDAT Souceforge: https://sourceforge.net/projects/epidat/ Wikipedia: https://es.wikipedia.org/wiki/Epidat -
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PMM-Lab
Predictive Microbial Modeling plug-in for KNIME
...It consists of three components: • a library of KNIME nodes (called PMM-Lab), • a library of “standard” workflows • an HSQL database.to store experimental data and microbial models. Altogether these components are designed to ease and standardize the statistical analysis of experimental microbial data and the development of predictive microbial models (PMM). Users can apply PMM-Lab to proprietary or public data and create bacterial growth / survival / inactivation models. The framework can easily be extended to other model types, e.g. growth/no-growth boundary models. PMM-Lab has been initiated and provided by the Federal Institute for Risk Assessment - BfR (Berlin, Germany). ... -
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SCaVis
Scientific Computation and Visualization Environment
...The program is fully multiplatform (100% Java) and integrated with Java and a number of scripting languages: Jython (Python), Groovy, JRuby, BeanShell. SCaVis can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential equations. Linear, non-linear and symbolic regression are also available. Elements of symbolic computations using Octave/Matlab scripting are supported. The project was migrated to DataMelt. -
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A collection of code, bundled into a single R package, to perform several aspects of data management, image pre-processing, data analysis and statistical inference related to the quantitative analysis of dynamic contrast-enhanced MRI (DCE-MRI).
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neural network designer
a dbms for neural nets. Chatbots, DTrees, random forests, n-grams,...
...With the designer, you are able to create different types of decision trees, random forests, n-grams, pattern-matchers, conversational agents and all sorts of AI related algorithms. You can combine statistical approaches as well as pattern matchers or others. Do natural language processing, image or data analysis & interpretation,... -
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PythonStatsLab
A collection of useful statistical functions written in Python
There are functions for numerical integration of the standard normal probability distribution. They can be used to find probabilities, find z-alpha values, calculate confidence interval, etc. New functionality I wish to add are hypothesis testing and calculation of p-value, type I & II errors, etc. These functions would come in handy to anyone taking introductory or intermediate-level courses in probability, statistics and data analysis. There are several numerical integration techniques... -
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EnvStats
An R Package for Environmental Statistics
...The EnvStats package, along with the R software environment, provides comprehensive and powerful software for environmental data analysis. EnvStats brings the major environmental statistical methods found in the literature and regulatory guidance documents into one statistical package, along with an extensive hypertext help system that explains what these methods do, how to use these methods, and where to find them in the environmental statistics literature. Also included are numerous built-in data sets from regulatory guidance documents and the environmental statistics literature. ... -
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Compositional data analysis, following the approach introduced by John Aitchison, is not straightforward to use with standard statistical packages. CoDaPack provides a software capable of using the Aitchison methodology.
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JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition.
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jHepWork
jHepWork was a name of the DataMelt program in 2005-20013
jHepWork (2005-2013) was an environment for scientific computation, data analysis and data visualization for scientists, engineers and students. The program is fully multiplatform (100% Java) and integrated with the Jython (Python) scripting language. Currently the project is known under the name DataMelt (https://datamelt.org)
