It provides tools for the manipulation and analysis of data throughout the process of predictive data mining. From data capture to multivariate model design, and from the specification of solutions to these models to their comparison and storage for later use, under a powerful and intuitive graphical user interface.

Data Acquisition and File Support
Auguri will read data from most sources in ANSI or binary format, in addition to its own format. It also supports drag and drop and copy and paste operations to and from most popular editors and spreadsheet programs.

In addition, we are working to comply with the Predictive Model Markup Language (PMML), for models supported by our software, and in interfaces to some of the most popular audio and image file formats.

Data Inspection, Editing and Visualization
Auguri allows opening multiple document files simultaneously for editing, inspection, charting, analysis or forecasting. It maps data to worksheets, where a worksheet may consist of one or several sheets containing additional data, models, solutions and reports.

Data may be edited freely and charted at will in most popular formats. Not only can you instruct Auguri to plot your data in 3-dimensions, but produce fully functional four-dimensional representations that can be zoomed, rotated, or even animated, if you so desire.

It also includes modern interpolation techniques for the replacement of missing values, or for resampling of existing data where additional information is desirable before continuing with further analysis.

In addition, Auguri provides several methods for the automatic generation of constant and serial data in your documents.

Statistical, Frequency, Linear and Nonlinear Analysis
Other than common statistical analysis methods such as ANOVA, test of means and variances, histograms, IID tests and descriptive statistics to the fourth moment, Auguri provides extensive nonlinear methods such as generalized fractal dimensions, Poincare surface of sections, maximal Lyapunov exponent, false nearest neighbors, space-time separation plots, averaged mutual information, and phase portraits in up to four-dimensions, among other.

It also provides 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 functions, time-evolving statistics, and simultaneous solutions to linear equations.

In addition, it includes several methods for the generation of random numbers according to a chosen distribution, for sampling data from existing populations, and for generating surrogate data, where statistical and nonlinearity tests may be additionally carried.