DARWin - Data Analysis ROBOT |
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DARWin is a complete algoritmic matrix-oriented high-level language for applications in research, science, technology, quality control and education. DARWin offers wide range of system and programming tools for data filtering and pre-conditioning, data analysis, statistical modelling, graphical insight and presentation, analytical reporting, database operations with SQL-support, process simulation and optimization, automation of data processing and state-of-the-art reporing, specialized analyses, development and codification of operation procedures, customized analytical modules, development and seamless implementation of new algorithms, technical and engineering education support, etc. DARWin is a part of the interactive statistical package QCExpert, it uses QCExpert´s resources, modules and data management. This connection extremely increases the system´s productivity and also range of problem it can readily solve. Steep learning curve enables the happy user almost instantly exploit the infinite possibilities of the QCExpert/DARWin system.
Free libraries, manuals and informations Downloads ![]() Communication with databases and data sources Programmed model-based data filtration Data diagnostics, fault detection and identification QC, SPC, Capability, R&R, MSA, DOE, SixSigma Automatic programmable PDF reporting Process optimization, identification of financial sources ![]() Training, courses, consulting, support On-line application libraries, development, maintenance Intuitive user environment and context help Unlimitted data size and flexible data structures Natural and easy scalability of applications Fast solution of complex and special problems Maximal effectivity with user function libraries Easy integration in menu and fast data connectivity Simulation and validation tools for advanced models Instant use, distribution and sharing of modules and functions ![]()
Data
Fast and effective access to diverse data sources. Transformations, filtering, validation, diagnostics. Free or model-based segmentation and categorization of data. Sorting, ordering, aggregating, random sampling. Measurement validation, fraud detection. Trend and structure identification, data pattern recognition methods. Processing large databases in "BigData" mode. Data smoothing, imputation and predictive missing data management with model-based approach. Time base regularization. Import/Export to databases and files. Tables, summary, surveys, graphics. Identification and filtration of outliers and invalid data.
Graphics
Diagnostic plots, combined informative plots, presentation graphics, structural plots, maps, network and tree plots, descriptive diagrams, histograms, splines, polygons, bars, 3D-dot plot, 3D functional surfaces, density, interactive 3D-plot mode, customizable graphics.
Statistics
Basic statistical functions, quantiles and probabilities of common distributions, parameter estimation, moments of a distribution, random process simulation from a given parametric distribution, density, confidence intervals. Parametric and nonparametric tests. Customized tests. Distribution mixtures, seqencial tests, robust methods. Multivariate statistical models, maximal likelihood estimates.
Mathematics
Basic mathematical functions, fast vectorized aritmetics, linear algebra, determinants, SVD, eigenvalues and eigenvectors, inverse and pseudoinverse, Choleski decomposition. Matrix computation. Full data indexing. Logical and arithmetical indices. Fast data operations. Numerical methods, nonlinear optimization, signal analysis, smoothing, spectral analysis.
Programming
Program flow control structures, conditional structures, interaction with operating system (DOS call). Scheduled program execution. Interactive tools for routine use of program: dialog windows, menu, messages, automated sending e-mails, automatic structured PDF reports. Intuitive development environment. Simple but powerful programming language. Masisve increase in productivity for many data-oriented processes. Extensive and expandable add-in user libraries. Scaling-up applications to fit actual data environment and needs.
Modelling
Methods and libraries for optimization, construction and deployment of statistical models. Advanced predictive models including Principal Component Regression, Neural Network, Support Vector Machines, multivariate linear and nonlinear regression, nonparametric local regression, time series and forecasting, model diagnostics, robust regression models, principal component analysis.
Applications
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Support
Assistance and support for users, pilot programs, design and development of tailored applications, customized data analyses, reports, recommendations, on-line consulting, design and implementation of new operating procedures for optimal control and analysis of data. Maintained modules and functions library.
Education
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Last Updated ( 18.03.2013 ) |