Solo empowers scientists and engineers with a host of point-and-click data-discovery tools including PLS, PCA and many other multivariate methods. It includes the main PLS_Toolbox graphical user interfaces, but MATLAB is not required! Import data from a variety of different file types and quickly assemble it into convenient DataSet objects to easily manage labels, axis scales, and classes. Include/exclude data from the analysis with just a click. Drag-and-drop data to our comprehensive Analysis window for modeling and analyzing results. Our integrated modeling guide and access to a large number of analysis and preprocessing techniques makes this graphical user interface environment appropriate for novice and expert users alike.
KEY METHODS INCLUDED:
- Data Exploration and Pattern Recognition (Principal Components Analysis (PCA), Parallel Factor Analysis (PARAFAC), Multiway PCA…)
- Classification (SIMCA, k-nearest neighbors, PLS Discriminant Analysis, Support Vector Machine Classification, Clustering (HCA)…)
- Linear and Non-Linear Regression (PLS, Principal Components Regression (PCR), Multiple Linear Regression (MLR), Classical Least Squares (CLS), Support Vector Machine Regression, Artificial Neural Networks, N-way PLS, Locally Weighted Regression…)
- Self-modeling Curve Resolution, Pure Variable Methods (Multivariate Curve Resolution (MCR), Purity (compare to SIMPLSMA), CODA_DW, CompareLCMS…)
- Curve fitting and Distribution fitting and analysis tools
- Instrument Standardization (Piece-wise Direct, Windowed Picewise, OSC, Generalized Least Squares Preprocessing…)
- Advanced Graphical Data Set Editing and Visualization Tools
- Advanced Customizable Order-Specific Preprocessing (Centering, Scaling, Smoothing, Derivatizing, Transformations, Baselining…)
- Missing Data Support (SVD and NIPALS)
- Variable Selection (Genetic algorithms, IPLS, Selectivity, VIP…)
MAC OSX (Intel), Linux, Windows XP, VISTA, Win7, Win8, or Win10. 250 MB of disk space and a recommended minimum of 500 MB of RAM (more may be necessary for some data) and a minimum of 16 bit color graphics are also required.
Eigenvector Research offers user support for Solo by e-mail at firstname.lastname@example.org. Questions are almost always answered within 24 hours (and usually much less). Updates and bug fixes can be downloaded from our web site. For information on other support options
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