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.
GPU based Parallel Gene-Gene Interaction Analysis
Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs) have multiple cores, whereas Graphics Processing Units (GPUs) also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic interaction analysis for binary traits. Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. Citation: Chikkagoudar, S., Wang, K., & Li, M. (2011). GENIE: a software package for gene-gene interaction analysis in genetic association studies using multiple GPU or CPU cores. BMC research notes, 4(1), 158.
GUANO - Graphical User interface for performing ANalysis Of variance
Free and open source standalone program capable of conducting between, within, and mixed analyses of variance (ANOVA). Provides a simple graphical user interface for specifying analyses and interaction plots (analyses performed by http://code.google.com/p/pyvttbl/). Features: - Capable of high order factorial designs (> 2 factors) - Within and mixed analyses of variance provide corrections for violations of sphericity (Huynh-Feldt, Greenhouse-Geisser, Box) - A variety of data transformations can be applied (log10, reciprocal, arcsine, square-root, and Windsor) - Generalized eta-squared measures of effect size - Post-hoc power analysis (should match G*Power) - Outputs include tables of estimated marginal means - Up to 4-way interaction plots with errorbars (png, svg) - Confidence intervals account for within-subject variability (where applicable; Loftus and Masson, 1994) - Non-proprietary HTML output files - Non-proprietary codebase Gotchas: - Assumes balanced designs
All future developments will be implemented in the new MATLAB toolbox SciXMiner, please visit https://sourceforge.net/projects/scixminer/ to download the newest version. The former Matlab toolbox Gait-CAD was designed for the visualization and analysis of time series and features with a special focus to data mining problems including classification, regression, and clustering.
A software directed towards the geomatics engineering community. OpenSSG efficiently implements a collection of components vital to geomatics industry using smooth and flexible interface.
GpaNom is a simple command line GPA calculator, written in C, with the goal of being fast and precise.
Graphx - simple plotter for students and pupils of high school. The project source on github.com: https://github.com/Armenian/graphx
A versatile MCMC and downhill optimization engine
Hrothgar is a parallel minimizer and Markov Chain Monte Carlo generator by Andisheh Mahdavi of San Francisco State University. It has been used to solve optimization problems in astrophysics (galaxy cluster mass profiles) as well as in experimental particle physics (hadronic tau decays). It is probably adaptable enough to be applied to your merit function if you can write it in C.
This material enables IBM SPSS Statistics users to run code written in the R language inside Statistics. Additional free items for R in Statistics and other materials are available from the SPSS Community at www.ibm.com/developerworks/spssdevcentral
IterInt is a numerical integration package that implements iterated numerical integration methods. Iterated methods can be used to compute low dimensional (less than ten, for example) integration problems to get very accurate results.
Java library of statistical distribution
A Java package that provides routines for various statistical distributions. Based on R version 2.14.1 (continuously updated; current as of R v3.3.0). The major difference is that JDistlib is thread safe. The library contains the density (pdf), cumulative (cdf), quantile, and random number generator (RNG) routines of the following distributions: Ansari, Beta, Binomial, Cauchy, Chi square, Exponential, Fisher's F, Gamma, Geometric, Hypergeometric, Kendall, Logistic, Log normal, Negative binomial, Noncentral beta, Noncentral chi square, Noncentral f, Noncentral t, Normal, Poisson, Sign Rank, Spearman, Student's T, Tukey, Uniform, Weibull, Wilcoxon, and many more. Normality tests, such as: Kolmogorov-Smirnov, Anderson-Darling, Cramer-Von Mises, D'Agostino-Pearson, Jarque Bera, Kolmogorov-Lilliefors, Shapiro-Francia, Shapiro-Wilk. And many others.
JStats is a Java application/applet for statistical testing.
JStats is a small but powerful Java application/applet for conducting statistical tests. The following tests are supported: * Parametric tests: T-test, ANOVA, Repeated Measures ANOVA * Non-parametric tests: Wilcoxon Rank-Sum, Wilcoxon Signed-Ranks, Kruskal-Wallis, Friedman * Check if datasets are normally distributed: Jarque-Bera, Shapiro-Wilk * Check if datasets have equal variances: F-test, Bartlett's test, John, Nagao and Sugiura's test * Correlation: Correlation coefficient, Spearman Rank correlation, linear regression * Confidence intervals test * Outliers: Generalized Extreme Studentized (ESD) test, outliers in ANOVA The latest version is available as applet on http://aiguy.org/Statistics.html
Kaplan-Meier for Windows
KMWin (Kaplan-Meier for Windows) is a convenient tool for graphical presentation of results from Kaplan-Meier survival time analysis. The programme is based on the statistical software environment R and provides an easy to use graphical interface. As an introduction, see http://dx.plos.org/10.1371/journal.pone.0038960#s2.
KinetDS is a software for curve fitting particularly designed for kinetic (mechanistic and empirical) description of a substance dissolution from solid state. It was primarily designed for handling pharmaceutical dissolution tests
An R package for detailed inspection and analysis of LCMS data. An R package developed by Sukhdeep Singh at Department of Surgery and Cancer, Imperial College London,UK.
Automatic Time Series Analysis with Stationary VAR Models
LDT is designed for automatic time-series analysis. Current version focuses on stationary vector autoregressive models (VAR) and the related analyses such as forecasting and Granger causality. See the following paper for an application: See http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2818213
Plot Excel data as photo-realistic 3D LEGO® models
Using a sequence of Open Source CAD/CAM and graphics tools, integrated through Excel macro code, "Lego Charts" extends the idea of the Excel 3-D bar chart. It allows the placement, shapes and colours of the bars to represent further dimensions to the data. The chart is presented as a photo-realistic model apparently constructed out of LEGO®  bricks. The downloaded package consists of an Excel template to create the charts, an extensive installation and user guide, and two fully-worked samples. Creating eye-catching Lego Charts is easy, fun, and rewarding! Platform: Windows 32 bit (XP onwards) with Microsoft Excel 2003 or later. For more information about Lego Charts, and how to install the package, please see the file README.txt on the the FIles page. ---  LEGO® and the LEGO logo are registered trademarks of The Lego Group, which does not sponsor, endorse, or authorize this software package or web page.
Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout
Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout (MAGeCK) is a computational tool to identify important genes from the recent genome-scale CRISPR-Cas9 knockout screens technology. For instructions and documentations, please refer to the wiki page. MAGeCK is developed and maintained by Wei Li and Han Xu from Dr. Xiaole Shirley Liu's lab at Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health. We thank the support from Claudia Adams Barr Program in Innovative Basic Cancer Research to develop MAGeCK.
Monte Carlo permutation method for SNP multiple test correlation
MCPerm: A Monte Carlo permutation method for multiple test correlation in case-control association study Traditional permutation (TradPerm) test is an important non-parametric analysis method which can be treated as the gold standard for multiple testing corrections in case-control association study. However, it relies on the original single nucleotide polymorphism (SNP) genotypes and phenotypes data to perform a large number of random shuffles, and thus it is computationally intensive, especially for genome-wide association study (GWAS). To improve the calculation speed without changing the size of the TradPerm p-value, we developed a Monte Carlo permutation (MCPerm) method as an efficient alternative to TradPerm. Methods: MCPerm does not need to shuffle the original genotypes and phenotypes data. It uses Monte Carlo method, employs two-step hypergeometric distribution to generate the random number of genotypes (AA, Aa and aa) in cases and controls.
A general recommender system with basic models and MRA
Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide controllable adjustment range, which thereby makes it possible to provide optional modes of recommendation aiming different kinds of users.
Math.NET aims to provide a self contained clean framework for symbolic mathematical (Computer Algebra System) and numerical/scientific computations, including a parser and support for linear algebra, complex differential analysis, system solving and more
A set of Matlab functions which compute effect size statistics and (exact) confidence intervals for a wide range of data analysis situations, including two-sample-, oneway-, twoway- and contrast analyses as well as categorical data in tables.
MinimPy is a desktop application program for sequential allocation of subjects to treatment groups in clinical trials by using the method of minimisation. Comprehensive reference help is available at: http://minimpy.sourceforge.net For those who have difficulty installing MinimPy, an online version is available at: http://qminim.sourceforge.net MinimPy has been full described in the foolowing article: Saghaei, M. and Saghaei, S. (2011) Implementation of an open-source customizable minimization program for allocation of patients to parallel groups in clinical trials. Journal of Biomedical Science and Engineering, 4, 734-739. doi: 10.4236/jbise.2011.411090. Available at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=8518
MonteCarlito 1.10 is a free, open-source Excel add in to do Monte-Carlo-simulations. It includes an introductory tutorial on Monte Carlo basics. It is licensed under GNU.