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CAMO Software Announce Pre-Release of a New Version of Their Multivariate Data Analysis and Design of Experiments Software, The Unscrambler® X version 10.2

  •     Exploratory data analysis: Principal Component Analysis (PCA), Cluster analysis (including K-means and Hierarchical clustering), Multivariate Curve Resolution (MCR)
  •     Regression methods: Principal Component Regression (PCR), Partial Least Squares (PLS), L-PLS, Support Vector Machines (SVM)
  •     Classification methods: Soft Independent Modeling of Class Analogy (SIMCA), Linear Discriminant Analysis (LDA), PLS-DA, SVM-C
  •     Design of Experiments: Plackett-Burman, Factorial, Central Composite, Box-Behnken, Mixtures, D-Optimal designs
  •     Pre-processing: Smoothing, Multiplicative Scatter Correction (MSC/EMSC), Orthogonal Signal Correction (OSC), Savitzky-Golay, COW, Additive & Multiplicative Baseline Correction methods
  •     Descriptive statistics and classical statistical tests

Brad Swarbrick, Vice President of Product Development at CAMO Software, says “The Unscrambler® X 10.2 makes data mining and analysis even easier for our scientific, research and engineering users. We have focused on increased ease of use, better data handling capabilities and added a number of useful features.”

Enhancements include the addition of block weighting for developing models suited to process manufacturing industries. For spectroscopy users, three new vendor specific imports have been included as well as more validation options for greater data interpretability.

The Unscrambler® X 10.2 is available for pre-order from CAMO Software’s international sales offices. There will be a series of free webinars to demonstrate the new version in February and March. Current users of The Unscrambler® are encouraged to upgrade to the new version.

A 30-day trial version of The Unscrambler® X 10.2 will be available for download from the 7th of March at http://www.camo.com.

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For the original version on PRWeb visit: http://www.prweb.com/releases/prwebcamo/multivariatedataanalysis/prweb9207884.htm

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