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- Flexibility to organise your data & analyse into projects
- Flexibility with licensing options
- Flexible in customization of
The Unscrambler® with plugin
options
Adaptable to the needs of the many different scientific disciplines through the incorporation of application specific plug-ins. Incorporate The Unscrambler® models into 3rd party applications.
Support vector machine classification and L-PLS, the classical hierarchical cluster analysis and linear discriminant analysis, which widen our scope to metabolomics, sensometrics and process monitoring.


Password access, windows domain authentication and audit trails provide the necessary security requirements for the regulated environment.
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| Better understand your products and processes through designed experiments and multivariate modelling. |
Maximize the benefits of The Unscrambler® models by using them in conjunction with our 3rd party partners, software platforms and instrumentation. |
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| Smarter designs use less resources and result in more information. Use this information to eliminate unnecessary measurements and maximize ROI |
Measure only what is critical to quality by using The Unscrambler® models for Multivariate Statistical Process Control (MSPC) applications |
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Descriptive Statistics Mean/ Std Dev/ Quartiles/ Cross Correlations/ Scatter EffectsStatistical Tests Normality Test/ t-Tests/ F-Tests/ Mardia’s Multivariate TestCluster Analysis K-means / K-medians Ward’s methodHierarchical Cluster Analysis (HCA) with dendrograms Principal Component Analysis (PCA) Choice of using NIPALS or SVD algorithmsRotation methods including Varimax, Equimax, Quartimax and Parsimax Multivariate Curve Resolution (MCR) Resolve time evolving data such as chemical reaction or chromatographic data into pure constituent profiles and pure spectra |
Regression Methods Multiple Linear Regression (MLR) / Principal Component Regression (PCR) and Partial Least Squares Regression (PLSR)Choice of algorithms, NIPALS and SVD for PCR and NIPALS, Kernel Methods and Orthogonal Scores for PLSR Improved Test Set Validation options Q-Residuals in influence plots L-PLS, incorporating three data tables for greater insights into data structure Advanced Classification Methods Projection using PCA and PLS modelsSoft Independent Modelling of Class Analogy (SIMCA) now also incorporating PLS models Linear Discriminant Analysis (LDA) Support Vector Machines (SVM) Classification with numerous kernel types |
Spectral Functions Smoothing Spectroscopic: Reflectance/ Transmission/ Kubelka-Munck Scatter Correction and Advanced Functions Multiplicative and Extended Multiplicative Scatter Correction (MSC/ EMSC)Standard Normal Variate (SNV) Deresolve Detrending General Transforms Improved Centre and Scale optionsSpectroscopic: Reflectance/ Transmission/ Kubelka-Munck Interaction & Squares and Individual Variable Weighting Compute General Fill Missing Values Correlation Optimization Warping (COW) |
Improved Design Wizard Interactive design setup with full descriptions and Beginner/ Expert modesComplete range of full and fractional factorial designs Enhanced optimization designs including Central Composite (CCD) and Box-Behnken (BB) designs Enhanced mixture designs including Axial, Simplex Lattice and Simplex Centroid designs Choice of Analysis Algorithms Classical MLR and ANOVA-PLS for non-orthogonal designsPLSR or Scheffe Polynomials for mixture designs Comprehensive Analysis Overview ANOVA tables and other tabular resultsCube Plots Response Surfaces Analysis of Effects Interactive Tables |
Pharmaceuticals
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Energy
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Chemicals
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Food & Beverages
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