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SOLO provides the Graphical Interfaces for quickly managing and analyzing data, authoring and applying models and interpreting results. Data can be imported from a variety of different file types and quickly assembled into convenient DataSet objects. Once in a DataSet object the user can easily manage labels, axis scales, and classes and can include/exclude data from the analysis with a click. Modeling and analyzing results is just a matter of drag-and-drop of the data to our comprehensive Analysis GUI.
SOLO provides the Graphical Interfaces for quickly managing and analyzing data, authoring and applying models and interpreting results. Data can be imported from a variety of different file types and quickly assembled into convenient DataSet objects. Once in a DataSet object the user can easily manage labels, axis scales, and classes and can include/exclude data from the analysis with a click. Modeling and analyzing results is just a matter of drag-and-drop of the data to our comprehensive Analysis GUI.
MATLAB Connection Tools
The PLS_Toolbox is a collection of advanced chemometric routines, i.e., tools designed specifically for modeling data from chemical systems. Originally named for the partial least squares (PLS) routines that have become a mainstay for calibration model development, the PLS_Toolbox now contains over 100 functions that can be used in a variety of technical areas. This includes linear and nonlinear modeling tools, along with functions that help the user apply them in the chemical laboratory or process environment. Tools included in the toolbox are point and click graphical user interfaces for principal components analysis and partial least squares regression and a suite of tools for the analysis of multi-way data.
With MIA_Toolbox, multivariate images from remote sensing to microscopy can be easily analyzed using the same PLS_Toolbox tools you are already familiar with. MIA_Toolbox allows you to load, manipulate, and analyze multivariate images in the Analysis Graphical interface as well as using many of the higher-level command-line functions. Principal components analysis, multivariate curve resolution, SIMCA and PLSDA classification, K-Means clustering, and even regression can all be performed on images with this extension pack.
Extended Multiplicative Scatter Correction (EMSC) is a powerful preprocessing technique used to isolate and remove complicated multiplicative and additive effects, such as those caused by light scattering in reflectance spectroscopy. It expands on the popular Multiplicative Scatter/Signal Correction (MSC) technique by offering much improved flexibility in identifying known interferences to remove as well as scaling targets and known analyte spectra. Eigenvector Research is offering this powerful patented technique as an add-on for use with PLS_Toolbox as EMSC_Toolbox.
Model_Exporter converts models created within the PLS_Toolbox or Solo chemometrics modeling environments into an interpretable format for use outside of these products.
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Extending suite of chemometric tools into
Multivariate Image Analysis!

SOLO provides the Graphical Interfaces for quickly managing and analyzing data, authoring and applying models and interpreting results. Data can be imported from a variety of different file types and quickly assembled into convenient DataSet objects. Once in a DataSet object the user can easily manage labels, axis scales, and classes and can include/exclude data from the analysis with a click. Modeling and analyzing results is just a matter of drag-and-drop of the data to our comprehensive Analysis GUI.

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Multivariate Image Analysis (MIA) toolbox expands the already expansive PLS_Toolbox functionality by including many image-specific functions and builds on PLS_Toolbox interfaces to make analysis of multivariate images simple and intuitive.

With MIA_Toolbox, multivariate images from microscopy to remote sensing can be easily analyzed using the same PLS_Toolbox tools you are already familiar with. MIA_Toolbox allows you to load, manipulate, and analyze multivariate images in the Analysis graphical interface as well as using many of the higher-level command-line functions. Principal components analysis, multivariate curve resolution (ALS and Purity), SIMCA and PLSDA classification, K-Means clustering, and even PLS or PCR regression can all be performed on images with this extension pack. MIA_Toolbox also adds a number of functionswhich are designed to take advantage of the special "spatial" relationship inherent in a multivariate image including functions like Evolving Window Factor Analysis and Maximal Autocorrelative Factors, and a suite of Texture functions.

MIA_Toolbox tools include...

  • "Automatic image display" technology to recognize and automatically present appropriate model results in image format.
  • Image importing and building functions to make assembly of multivariate images easier.
  • Image specific functions including EWFA, MAF, and an image-enhanced Cluster analysis.
  • Texture-analysis functions which encode the texture in an image into a vector for pattern or regression analysis.
  • Enables most standard PLS_Toolbox functions to work with images.
MIA_Toolbox is currently available in Version 1.0.5. This release delivers a number of bug fixes and plotting enhancements along with the use of images in the Purity analysis method.

System Requirements

MIA_Toolbox requires PLS_Toolbox version 4.1 or higher and MATLAB 6.5, 7.x or higher. MIA_Toolbox does not require other MATLAB toolboxes. Like most MATLAB toolboxes, MIA_Toolbox is platform independent. It will function on any platform on which MATLAB functions (e.g. MAC, PC, Unix).

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