Open Source Statistics Software - Page 5
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Auth0 for AI Agents now in GAConnect your AI agents to apps and data more securely, give users control over the actions AI agents can perform and the data they can access, and enable human confirmation for critical agent actions.
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Free and Open Source HR SoftwareGive your HR team the tools they need to streamline administrative tasks, support employees, and make informed decisions with the OrangeHRM free and open source HR software.
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CoLabR
A simple user interface to the R software environment.
A simple user interface to the R software environment. It is designed for people new to R and provides the user with easy access to their variables and data along with pointers to the most basic commands. It also allows for multiple people to share data across different sessions on different machines. In this way it also offers a collaborative environment for people to work together in remote locations. -
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Community Detection Modularity Suite
Suite of community detection algorithms based on Modularity
- MixtureModel_v1r1: overlapping community algorithm [3], which includes novel partition density and fuzzy modularity metrics. - OpenMP versions of algorithms in [1] are available to download. - Main suite containing three community detection algorithms based on the Modularity measure containing: Geodesic and Random Walk edge Betweenness [1] and Spectral Modularity [2]. Collaborator: Theologos Kotsos. [1] M. Newman & M. Girvan, Physical Review, E 69 (026113), 2004. [2] M. Newman, Physical Review E, 74(3):036104, 2006. [3] B. Ball et al, An efficient and principled method for detecting communities in networks, 2011. The suite is based upon the fast community algorithm implemented by Aaron Clauset <aaron@cs.unm.edu>, Chris Moore, Mark Newman, and the R IGraph library Copyright (C) 2007 Gabor Csardi <csardi@rmki.kfki.hu>. It also makes of the classes available from Numerical Recipies 3rd Edition W. Press, S. Teukolsky, W. Vetterling, B. Flanne -
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Corbata
CORe microBiome Analysis Tools
Corbata is a set of statistical tools that can be used to analyze the core microbiome across a set of samples. -
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Criterial
The package for statistical data analysis and applied mathematics
Putting truth before show-off. The high performance open source package for statistical data analysis and applied mathematics Criterial is an add-in for all desktop versions of the LibreOffice Calc spreadsheets on any 64-bit operating systems. The combination of the unsurpassed convenience of spreadsheets as frontend and the maximum speed of the C++ programming language as backend. Contains user experience and the best ideas of projects AtteStat and StatAnt. Completely free. No donation required. Criterial comes with absolutely no warranty. The software is not certified for use in healthcare. Please do not use this software for purposes related to diagnosing diseases or making treatment decisions. The software is not certified in the European Union. Please do not download, distrubute or use the software in countries of the European Economic Area. -
Web-Based Debt Collection SoftwareInterProse ACE is a modern, web-based debt recovery software solution built for collection agencies who specialize in consumer or commercial debt, including property management, healthcare, education, and government accounts.
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A collection of small utilities with a connection to cryptography and cryptanalysis. Written for efficiency and a small memory footprint.
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CvHMM
Discrete Hidden Markov Models based on OpenCV
This project (CvHMM) is an implementation of discrete Hidden Markov Models (HMM) based on OpenCV. It is simple to understand and simple to use. The Zip file contains one header for the implementation and one main.cpp file for a demonstration of how it works. Hope it becomes useful for your projects. -
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Software to cluster protein sequences into functionally similar groups. Journal reference: http://bioinformatics.oxfordjournals.org/cgi/content/short/24/16/1765
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Data Mining Platform is a platform for data mining and analysis. It contains many of the new and sophisticated methods such as kernel-based classification, two-way clustering, bayesian networks, pattern recognition for time series analysis and many other
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Securely stream and govern industrial data to power intelligent operations with agentic insights.Trusted MQTT Platform — Fully-managed and cloud-native MQTT platform for bi-directional IoT data movement.
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DataPrep
Python-based data preprocessing tool
DataPrep v0.2 is a Tkinter-based GUI application/tool designed to assist users in data preprocessing, multicollinearity removal, and feature selection for a wide range of applications in Cheminformatics, Bioinformatics, Data Analysis, Feature Selection, Molecular Modeling, Machine Learning, and Quantitative-structure-property relationship (QSPR) studies. It includes functionality to load, process, and save datasets with support for different preprocessing & multicollinearity removal strategies with customizable parameter setting options. -
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DeDAY
MLE survival analysis: Gompertz, Weibull, Logistic and mixed morality.
DeDAY (Demography Data Analyses) is a tool of analyzing demography data. It supports Gompertz, Weibull and Logistic distributions. DeDay also supports mixed mortality models based on these distribution such as the Gompertz-Makeham distribution. Distributions such as Gompertz describes only age-dependent mortality, which increases over time. Mixed mortality models, such as in Gompertz-Makeham distribution, consider a more general case where mortality is consist of both age-dependent and in-dependent mortality. Mixed models partition mortality into exogenous and endogenous components, so that the intrinsic survivorship can be estimated without the interference from extrinsic noise. DeDAY supports both interval-censored data and exact event-time data. Using MLE (Maximum Likelihood Estimate), DeDAY fits statistic model to the data. DeDAY also calculates the variances and the multi-dimensional confidence limits of model parameters. DeDAY is free for academic users. -
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Diagonal
A command line toolki to solve a problem your favorite program defines
Diagonal can be used for: - getting descriptive statistics such as mean/median/mode with your program producing a sample - finding a root of an equation your program defines - calculating a fixed point of a function your program defines - detecting a cycle of a fuction your program defines as well as - decoding a VCDIFF file -
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DissoKin
Dissolution Kinetics Software Excel Based
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A project aims to develop a system which trains LDA model in distributed enviorenment. I studied Hadoop based solution and found that Hadoop is not fit for distributed LDA training case. In this project I implement a platform based on socket.
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"DoomsdayCalculator" is based on the doomsday argument and allows the user to calculate minimum and maximum expected remaining lifetimes at a certain confidence level.
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DyMMM
Dynamic Multispecies Metabolic Modeling framework
The Dynamic Multispecies Metabolic Modeling (DyMMM [dĭm]) framework is a mathematical modeling tool that integrates multiple constraint-based metabolic models into a single dynamic community metabolic model. The DyMMM framework was formerly known as the DMMM framework. Please use the following citation for bibliographical purposes: Zhuang, K., Izallalen, M., Mouser, P., Richter, H., Risso, C., Mahadevan, R., & Lovley, D. R. (2011). Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments. The ISME journal. Zhuang, K., Ma, E., Lovley, D. R., & Mahadevan, R. (2012). The design of long-term effective uranium bioremediation strategy using a community metabolic model. Biotechnology and Bioengineering. -
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The EconoMind is a utility that simulates the economy of a city, state, country, or planet at a specific level of technological development. It runs behind the scenes and provides supply, demand, and other information for games and other projects.
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The procedure of building the environment of Emacs + ESS for R is more complicated, so we exploit the automated installation software that combines R, Emacs and ESS to let the the public download and install.
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EnvStats
An R Package for Environmental Statistics
EnvStats is an R package for environmental statistics. It is the open-source successor to the commercial module for S-Plus© called "EnvironmentalStats for S-Plus", which was first released in April, 1997. 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. EnvStats combined with other R packages (e.g., for spatial analysis) provides the environmental scientist, statistician, researcher, and technician with tools to “get the job done!” -
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Herramienta gratuita para crear estadísticas de forma sencilla. Estadística Fácil es una aplicación desarrollada para permitirte crear tablas al estilo de las de Excel.
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This project adds a ribbon to excel with a number of statistical buttons. This is not intended to be a full statistical analysis package (like R), but only a source for quick visualizations and calculations. For Excel2007 and up
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Excelsi-R
Excel's Interface to R
Excelsi-R is an Excel add-in that allows Excel spreadsheets to harness the power of the R statistical language by connecting to a running R process. R does not need to be installed on the computer running Excel, but it does require access to an R instance running Rserve (which can be on a remote computer). It supports incorporating R plots and graphs in an Excel workbook. -
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ExoPlanet
GUI based toolkit for running common Machine Learning algorithms.
ExoPlanet provides a graphical interface for the construction, evaluation and application of a Machine Learning model in predictive analysis. With the back-end built using the numpy and scikit-learn libraries, as a toolkit, ExoPlanet couples fast and well tested algorithms, a UI designed over the Qt4 framework, and graphs rendered using Matplotlib to provide the user with a rich interface, rapid analytics and interactive visuals. ExoPlanet is designed to have a minimal learning curve, allowing researchers to focus on the applicative aspect of Machine Learning rather than their implementation details. It provides algorithms for unsupervised and supervised learning, which may be done with continuous or discrete labels. Post analysis, the toolkit further automates building the visual representations for the trained model. -
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