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Application

 

Inspection and Visualization

 

Frequency Filter Design

 

Data Smoothing

 

Neural Network Training

 

Simulation Test

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Auguri? Features


Data Import and Export

  • ANSI Data Import and Export.
  • Binary Data Import and Export.
  • Copy and Paste.
  • Drag and Drop.

Data Editing, Formatting and Printing

  • Automated data population.
  • Complete functionality for editing, formatting, and printing.
  • Mixed data type support: Date, Text, Number, and Formula.
  • Find and Replace Operations.
  • Cut, Copy, and Paste.
  • Drag and Drop.
  • Sorting.

Charting

  • Multiple chart types: Line, Bar, Point, Surface, Contour, and so forth.
  • One-, two-, three-, and four-dimensional charts.
  • Conversion among compatible chart types.
  • Chart Animation and Movie Creation.
  • Chart formatting, printing, saving and exporting.

Data Model Definition

  • Easy model definition and specification.
  • Automatic embedding.
  • Automatic assignment of values for dates and text.
  • Unlimited number of concurrent model solutions.
  • Multivariate Models of up to 8,192 vectors of 1,024 elements each and 4,194,303 instances.

Math Operations Between Series

  • Addition.
  • Subtraction.
  • Multiplication.
  • Division.
  • Logical AND.
  • Logical OR.
  • Logical XOR.

Analysis Tools

  • One- and two-factor Analysis of Variance.
  • Auto and cross Average Mutual Information.
  • Auto and cross Covariance and Correlation Functions.
  • Chi-Square Test for one Population Variance.
  • Descriptive Statistics: Mean, Median, Mode, Geometric Mean, Harmonic Mean, Mean Deviation, Root Mean Square, Variance, Standard Deviation, Sample Variance, Sample Standard Deviation, Standard Error, Skewness, Standard Error of Skewness, Kurtosis, Standard Error of Kurtosis, Count, Sum, Range, Minimum, Maximum, Confidence Interval, and Additional Modes.
  • False Nearest Neighbors.
  • Frequency Domain Correlation.
  • Generalized Dimensions under different numerical methods: Ellner, Grassberger-Procaccia, Takens-Theiler, and so forth.
  • Histograms: Natural, Uniformly Binned, and Gaussian-Binned.
  • IID Tests: Box-Pierce, Difference-sign, Ljung-Box, McLeod-Li, Rank, and Turning Point.
  • Maximal Lyapunov Exponent: Kantz and Rosenstein methods.
  • One-Sample Tests for Means: t-Test and z-Test.
  • Poincare Surface of Section.
  • Power Spectrum Estimation: Periodogram, Averaged, Windowed, and Maximum Entropy.
  • Recurrence Analysis.
  • Running Statistics: Progressive or windowed for Mean, Root Mean Square, Variance, Mean Deviation, Standard Error, and Standard Deviation.
  • Simultaneous Solution of Linear Equations.
  • Space Time Separation Plot.
  • State Space Visualization (Phase Portraits) in up to 4-dimensions.
  • Two-Sample F-Test for Variances.
  • Two-Sample Tests for Means: t-Test and z-Test.

Operation Tools

  • User-defined functions with functional equation parser. These functions can be applied directly on the data and can be used as neural threshold functions in forecast solutions.
  • Window Functions: Barlett, Blackman, Blackman-Harris, Dolph-Chebyshev, Half-Cycle Sine, Hamming, Hann, Kaiser, Parzen, and Welch.
  • Difference and Summation of series.
  • Digital Filter Design: Sinc Function, Remez Exchange, and user-defined Frequency Custom.
  • Embedding.
  • Event Times and Times Event.
  • Exponential Smoothing.
  • Mixed Radix Real and Complex, Forward and Inverse Fourier Transforms for one or two dimensions.
  • Frequency Domain Convolution.
  • Numerical Interpolation and Resampling: Many methods for one- and multi-dimensional uniformly and arbitrarily spaced data.
  • Moving Average.
  • Data Normalization: Zero Mean One-Standard Deviation with optional scaling.
  • Numerical Differentiation for empirical data: Many methods for uniformly and arbitrarily spaced data.
  • Numerical Integration for empirical data: Many methods for uniformly and arbitrarily spaced data.
  • Polynomial Expansion.
  • Automated data population.
  • Random Number Generation in several distributions: Uniform, Beta, Binomial, Chi-Square, Exponential, F-Distribution, Gamma, Gaussian, and t-Distribution, among others.
  • Data Sampling (see Random Number Generation for possible sampling distributions).
  • Savitzky-Golay for uniform and arbitrarily spaced data.
  • Data Scaling.
  • Surrogate Data Generation: Random Shuffle, Phase-Randomized, Gaussian Scaled, Fourier Shuffled, Iterated Amplitude Adjusted, and Multi-Dimensional Fourier Transformed.

Table and Data Operations

  • Forced Text Removal.
  • Joining and Splitting.
  • Row and Column order reversal.
  • Text Value Classification.
  • Transposition.

Model Approximation and Forecasting Methods

  • Static Global Least Squares: Solution is based on a static data section.
  • Dynamic Global Least Squares: Solution data section changes dynamically according to the prediction point.
  • Global Multilayer Perceptrons: User Defined Feedforward Artificial Neural Networks.
  • Averaged or Weighted K-Nearest Neighbors.
  • Local Least Squares.
  • Local Averaged or Weighted Least Squares.
  • Local Multilayer Perceptrons.
  • Editing of Solutions.
  • Test Reports.
  • Forecast Error Analysis.
  • Interactive Tests and Simulations.
  • Simultaneous Comparison of Solutions.
  • Run Solutions against external data.
  • Formatted accounts of test results.

When it comes to data exploration and forecasting, Auguri is clearly your best choice.  As an analyst, you know that time equals money. Our software will help you be professional, profitable and productive.

You tell us what you want and we do it in the most technically advanced, precise and efficient way. Why settle with old expensive technologies when you can have the way of tomorrow today?


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