Open Source Linux Statistics Software - Page 4
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Chordalysis
Log-linear analysis (data modelling) for high-dimensional data
===== Project moved to https://github.com/fpetitjean/Chordalysis ===== Log-linear analysis is the statistical method used to capture multi-way relationships between variables. However, due to its exponential nature, previous approaches did not allow scale-up to more than a dozen variables. We present here Chordalysis, a log-linear analysis method for big data. Chordalysis exploits recent discoveries in graph theory by representing complex models as compositions of triangular structures, also known as chordal graphs. Chordalysis makes it possible to discover the structure of datasets with thousands of variables on a standard desktop computer. Associated papers at ICDM 2013, ICDM 2014 and SDM 2015 can be found at http://www.francois-petitjean.com/Research/ YourKit is supporting Chordalysis open source project with its full-featured Java Profiler. YourKit is the creator of innovative and intelligent tools for profiling Java and .NET applications. http://www.yourkit.com -
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Chuck Coleman's SAS Codes
SAS Codes
SAS codes for LMG variable importance, Box-Cox transformation including interactions. Documentation and PowerPoint slides. Directories under "Files" with descriptions: NESUG 2014: "A Fast, High-Precision Implementation of the Univariate One-Parameter Box-Cox Transformation Using the Golden Section Search in SAS/IML®" SESUG 2017: "Decomposing the R-squared of a Regression Using the Shapley value in SAS®" SESUG 2019: "Conditionally Executing Data Steps and Statements Based on the Presence of Variables in a SAS® Dataset" GASP 2020: "Online Winsorization of the Survey of Construction’s Price Estimates" My SESUG 2015 materials can also be found in my project "constrainingarrays" at https://sourceforge.net/projects/constrainingarrays/. -
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Stand-alone software tool for the interactive CE analysis of microarray data. The software is a user-friendly and allows on-the-fly study of CE
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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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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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DEAPathways
Differential Expression Analysis for Pathways
This project contains the source code associated with the PLoS Computational Biology publication: "Differential Expression Analysis for Pathways". The paper text can be found here: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002967 -
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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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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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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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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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FastPval is multiple stage p-value computing software that computes empirical p-values from a large set of permutated/resampled background data.
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FrancescoMontorsi ScientificResearch
Scientific research work of Francesco Montorsi,Univ. of Modena, Italy
This project hosts the code and the documents which were created by Francesco Montorsi during his PhD at the University of Modena and Reggio Emilia, Italy, about indoor and outdoor localization and navigation techniques. The code (mostly MATLAB code) is publicly available to enable reproducible research. -
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FreDec
Parallelized FREquency DEComposer algorithm
This is a parallelized algorithm performing a decomposition of the time-series data into a number of sinusoidal components, disentangling them from the white Gaussian noise. The algorithm analyses all suspicious frequencies, including the ones that look like an alias at a glance, but may become preferable later. After selection of the initial frequency candidates, the algorithm passes through all their possible combinations and estimates their multi-frequency statistical significance. In the end, it prints out the set of largest frequency tuples that were still found significant. The GPU computing is implemented through CUDA and brings a significant performance increase. It is still possible to run FreDec solely on CPU, if no suitable GPU device is available in the system. See the details of the underlying theory in Baluev 2013, MNRAS, V. 436, P. 807 The description of the algorithm itself can be found in arXiv:1309.0100. Please go to the project forum to report any bugs. -
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GADfit
Global nonlinear optimization with automatic differentiation
NOTE: Development continued at GitHub! Current version is higher than 1.2.0. GADfit is a Fortran implementation of global nonlinear curve fitting, based on a modified Levenberg-Marquardt algorithm. Global fitting refers to fitting many datasets simultaneously with some parameters shared among the datasets. The fitting procedure is very fast and accurate thanks to the use of automatic differentiation. The model curves (fitting functions) can be of essentially arbitrary complexity. This includes any nonlinear combination of elementary and special functions, single and/or double integrals, and any control flow statement allowed by the programming language. See the latest user guide under Files. -
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GIT quick statistics
An efficient way to access various statistics in git repository
git-quick-stats is a simple and efficient way to access various statistics in a git repository. Any git repository may contain tons of information about commits, contributors, and files. Extracting this information is not always trivial, mostly because there are a gadzillion options to a gadzillion git commands. For those who prefer to utilize command-line options, git-quick-stats also has a non-interactive mode supporting both short and long options. You can change to the legacy color scheme by toggling the variable _MENU_THEME between default and legacy. You can set variable _GIT_LIMIT for limited output. It will affect the "changelogs" and "branch tree" options. You can also exclude files from the stats. Note that it works with any alphanumeric, glob, or regex that git respects. -
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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.
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Gradesystem
Gradesystem
C programmed text-based software. Inputs : -Name of a course -Number of students -The 100% value of a mark -All the marks Then it estimates the Standard Deviation and grades, then assigns the marks to the grades inside a text. -
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Graphx
GraphxV1.1
Graphx - simple plotter for students and pupils of high school. The project source on github.com: https://github.com/Armenian/graphx
