About MIA Toolbox and Solo: Difference between revisions
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'''Solo+MIA''' Combines the functionality of MIA_Toolbox with our stand-alone graphical analysis application '''[[About_PLS_Toolbox_and_Solo|Solo]]'''. You can learn more about the Solo+MIA package from the [http://www.eigenvector.com/software/solo+mia.htm Eigenvector Research website]. | '''Solo+MIA''' Combines the functionality of MIA_Toolbox with our stand-alone graphical analysis application '''[[About_PLS_Toolbox_and_Solo|Solo]]'''. You can learn more about the Solo+MIA package from the [http://www.eigenvector.com/software/solo+mia.htm Eigenvector Research website] | ||
'''See the [[The_MIA_Toolbox_GUI_Environment|MIA_Toolbox and Solo+MIA Users Guide]] for more information on the features of MIA_Toolbox and Solo+MIA.''' | |||
==About MATLAB== | ==About MATLAB== | ||
A quick description or MATLAB can be found [[ About_PLS_Toolbox_and_Solo#About MATLAB | here]] | A quick description or MATLAB can be found [[ About_PLS_Toolbox_and_Solo#About MATLAB | here]] |
Revision as of 11:14, 5 December 2013
About MIA_Toolbox and Solo+MIA
MIA_Toolbox extends 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 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 functions which 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.
Solo+MIA Combines the functionality of MIA_Toolbox with our stand-alone graphical analysis application Solo. You can learn more about the Solo+MIA package from the Eigenvector Research website
See the MIA_Toolbox and Solo+MIA Users Guide for more information on the features of MIA_Toolbox and Solo+MIA.
About MATLAB
A quick description or MATLAB can be found here