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Download Partial Least Squares Toolbox v4.2.1 for Matlab keygen by iDK0DAY

Added to site2008-04-10

Partial.Least.Squares.Toolbox.keygen.zip (205915 bytes)

Partial.Least.Squares.Toolbox.keygen.exe 221184 204317
iDK0DAY.nfo 2070 1054


keygen for Partial Least Squares Toolbox v4.2.1 for Matlab by iDK0DAY



   Product:      Partial Least Squares Toolbox v4.2.1 for MATLAB
   Company:      Eigenvector Research, Inc.
   Release date: 04/10/08
   Rar count:    xx/5mb
   Supplier:     iDK
   Cracker:      iDK

   PLS_Toolbox is the world-recognized suite of essential and advanced chemometric multivariate 
   analysis tools for use within the MATLAB computational environment.

   PLS_Toolbox contains the tools required by chemical engineers, analytical chemists and other 
   analysis-driven scientists to explore their data and build predictive models. It gets its name 
   from the Partial Least Squares (PLS) regression method, which has become the standard calibration 
   method in many regression applications, but the toolbox now includes so much more including a 
   unified graphical interface and over 300 tools for use in a wide variety of technical areas. 
   Find out more about the latest release.
   PLS_Toolbox tools include...

    * Data Exploration and Pattern Recognition (Principal Components Analysis, Parallel 
      Factor Analysis, MCR, Purity, Tucker Models...)
    * Classification (SIMCA, k-nearest neighbors, PLS Discriminant Analysis, 
      Cluster Analysis with Dendograms...)
    * Linear and Non-Linear Regression (PLS, Principal Components Regression, N-way PLS, 
      Locally Weighted Regression...)
    * Self-modeling Curve Resolution, Pure Variable Methods (CODA_DW, Purity 
      (compare to SIMPLSMA), CompareLCMS...)
    * Curve fitting and Distribution fitting and analysis tools
    * Instrument Standardization (Piece-wise Direct, 
      Generalized Least Squares Preprocessing...)
    * Advanced Graphical Data Set Editing and Visualization Tools
    * Advanced Customizable Order-Specific Preprocessing (Centering, Scaling, 
      Smoothing, Derivatizing...)
    * Missing Data Support
    * Variable Selection (Genetic algorithms, IPLS, purity-based analysis)


   1. Unpack
   2. Run
   3. Enjoy this great Toolbox!

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