Search Results for "platform-tools"

PyMC is a Python library for probabilistic programming focused on Bayesian statistical modeling and machine learning. Built on top of computational tools like Aesara and NumPy, PyMC allows users to define models using intuitive syntax and perform inference using MCMC, variational inference, and other advanced algorithms. It’s widely used in scientific research, data science, and decision modeling.

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). ...

***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** Within the SIROCCO suite of numerical tools, the purpose of SDAP is to provide a flexible platform to carry out multivariate assimilation of geophysical data in a numerical model. The program is multi-grid (finite differences or finite elements), multi-algebra (plug-in analysis kernels), multi-model (simple standardized interface). The program supports reduced-order data assimilation methods, as well as Ensemble assimilation approaches such as the Ensemble Kalman Filter. ...

NAVAL-SEM is an award-winning, free and open-source offline Structural Equation Modeling (SEM) platform supporting PLS-SEM and CB-SEM workflows. Designed for researchers, PhD scholars, professors, and analysts, it provides visual model building, measurement assessment, structural model analysis, and reproducible research workflows without subscriptions or cloud dependency. Features include: • PLS-SEM & CB-SEM • Bootstrapping, mediation, moderation & conditional process analysis • HTMT, AVE, Composite Reliability, Cronbach's Alpha, Fornell-Larcker • VIF, f² effect size, indirect effects, Q² blindfolding, PLSpredict, CVPAT • Multi-Group Analysis (MGA), HOC, MICOM • IPMA, NCA, nonlinear effects, FIMIX-PLS, PLS-POS, endogeneity checks • EFA, CVI, measurement validation, fsQCA • APA report generation and R/Python/Lavaan export Fully offline and available for Windows, macOS, and Linux. ...

LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone.

TAVIA is a free and open-source desktop application for statistical analysis, scientific graphing, reproducible workflows, and research project management. It combines editable data tables, statistical tests, regression, dose-response analysis, publication-quality graphs, reports, project history, and reproducibility tools in one workspace. Analyses and graphs remain linked to their source data so results can be refreshed when data changes. TAVIA supports Windows, Linux, and macOS, includes a command-line analysis interface, encrypted project files, plugin support, automatic update checking, and built-in documentation. It is designed for researchers, students, laboratories, and analysts who want a local-first environment for managing data, analysis, visualization, and reporting. ...

Charting tools, backtesting tools, and data visualization tools for the most popular cryptocurrencies.

Software for speech research. It includes programs and libraries for signal processing, along with general purpose scientific libraries. Most of the code is in Python, with C/C++ supporting code. Also, contains code releases corresponding to publishe

This is Slycat - a web-based data science analysis and visualization platform, created at Sandia National Laboratories. The goal of the Slycat project is to develop processes, tools and techniques to support data science, particularly analysis of large, high-dimensional data.

This project hosts tools used for analysis of Gaussian Mixture Distributions (GMDs) which are used for statistical signal processing. The tools are libraries for implementing GMD operations and programs used to analyze properties of GMDs.