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Auguri is an integrated, general purpose data exploration, analysis and forecasting tool with emphasis on nonlinear methods. It provides tools for the manipulation and analysis of data throughout the process of predictive data mining.
Details: Analysis and Operations
Common statistical analysis methods such as ANOVA, test of means and variances, histograms, IID tests and descriptive statistics are standard. Auguri also provides nonlinear methods such as generalized dimensions, Poincare sections, maximal Lyapunov exponent, false neighbors, space-time separation, mutual information, and phase portraits, as well as tools for the analysis of signals and series in the time and frequency domains, such as power spectrum estimation, Fourier transforms, auto- and cross- covariance and correlation, time-evolving statistics, solutions to linear equations and methods for the generation of random numbers in various distributions, as well as data scaling, normalization, differencing, summation and operations between series and includes a powerful functional expression parser that can be applied directly to data.
Model Specification and Solutions
In Auguri, models are specified straightforward. No need to expand data to specify complex, multivariate dependencies. All data expansion takes place automatically, following specifications, with concurrent solutions to models, which can be simulated, compared, or ran with external data.
URL: aag-auguri.com
Category: Software Applications
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