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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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What's New in Version 5.0

Version 5.0 of PLS_Toolbox and Solo was released in October, 2008.

For general product information, see PLS_Toolbox Product Page. For information on Solo, see Solo Product Page.

NEW FEATURES

  • Analysis GUI has undergone a major renovation allowing for much more flexible data management, plot and data "linking" (connections between data and model results like selections and exclusions in scores and loadings), and data manipulation.
  • Analysis GUI now allows simultaneous loading of Calibration and Validation data and has a revised interface to make loading and working with data and models easier and more intuitive
  • Improved interactivity for multi-way data in Analysis GUI
  • Several preprocessing methods and options have been added including EPO, GLSW, windowed normalization, and baselining options.
  • Additional importing methods including a greatly improved automatic text importer and support for several Hamilton Sundstrand file formats
  • Improved editing, sorting, and visualization tools for DataSets
  • Model robustness tests in Analysis GUI and at the command line
  • Export model to "model building function" which can be used to reproduce a given model
  • New clustering method "dbscan"
  • Added "Color By" function for colorized plots and improved 3D visualization to Plot Controls.
  • Sorting of data by rows, columns, or any label field.
  • Simple "Open in Analysis GUI" option on any data to allow for simple multi-block analyses (e.g. combination of Scores from multiple models)
  • Improved missing data support (automatic exclusion of un-replaceable data)
  • Simplified window-docking options allow for "docking" all windows in a single Figures window.
  • Improved automatic factor selection
  • IPLSDA (Interval PLSDA variable selection) support
  • Batch and Wafer digestion support for "Batch" DataSet objects (supports different length batches)
  • New DataSet Object features (DSO version 5.1)

NEW FUNCTIONS AND FILES

asfreadr - Reads a Hamilton Sundstrand data file.
dbscan - Density-based automatic sample clustering.
encodemodelbuilder - Create MATLAB m-code which will regenerate a given model.
ils_esterror - Estimation error for ILS models.
matchrows - Matches up rows from two DataSet objects using labels or sizes.
testrobustness - Test regression model for robustness to various effects.
tsqqmtx - Calculates matrix for T^2+Q contributions for PCA and MPCA.
@dataset\sortby.m
@dataset\sortcols.m

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