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  • Software - Eigenvector Research, Inc.
    on the popular Multiplicative Scatter Signal Correction technique by offering much improved flexibility in selecting backgrounds to subtract known interferences as well as scaling targets and known analyte spectra Requires current version of PLS Toolbox Latest Release Notes DataSet Object DSO Standard Data Object for managing multivariate data in MATLAB When added to a MATLAB installation DSO creates a new object in MATLAB that integrates all of the separate components associated with a data set into a single variable in the MATLAB workspace It is applicable to any data which requires storing auxiliary information along with the data itself Prior to this breakthrough application created by Eigenvector there has been no standard way to associate all the parts of a data set that go together including the sample and variable labels class variables time and wavelength axes etc Latest Release Notes Other Products Floating License Server Floating License Server for PLS Toolbox and Solo Allows multiple users to share a single copy of PLS Toolbox or Solo Operates on a server located on site and issues temporary licenses to users as they need to use the software Latest Release Notes Stand Alone Software Solo Stand alone Chemometrics Software in a point and click environment Solo allows the user to perform PLS PCA and many other multivariate analyses independent of the MATLAB environment Solo includes the main PLS Toolbox graphical user 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 Modeling and analyzing results is just a matter of drag and drop of the data to the comprehensive Analysis GUI Latest Release Notes Solo MIA Solo with Multivariate Image Analysis functionality Solo MIA combines the stand along graphical

    Original URL path: http://www.eigenvector.com/software/index.htm (2016-04-27)
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  • PLS_Toolbox - Eigenvector Research, Inc.
    and build predictive models Key Methods Included Data Exploration and Pattern Recognition Principal Components Analysis PCA Parallel Factor Analysis PARAFAC Multiway PCA Tucker Models 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 Design of Experiment DOE tools for designing and analyzing experiments 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 Plus all the cutting edge tools you ve come to expect from Eigenvector Research All with source code allowing the advanced user to view and understand the techniques no more black box analyses Works How You Want and How You Need Most of the time users prefer to point and click their way through data editing and modelling tasks But sometimes users need to incorporate data crunching and visualization functions in their own MATLAB code in order to automate or customize analyses PLS Toolbox lets you work both ways It includes very sophisticated interfaces which allow users to tackle almost any modeling task But it also lets users access all the functionality via the command line with its powerful and well documented object oriented code Find out more about working with interfaces and about working with the command line System Requirements MATLAB 7 6 2008a or higher on all platforms supported

    Original URL path: http://www.eigenvector.com/software/pls_toolbox.htm (2016-04-27)
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  • MIA_Toolbox - Eigenvector Research, Inc.
    even PLS or PCR regression MIA Toolbox also adds functions 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 NOTE The functionality of MIA Toolbox is available in our stand alone product Solo MIA Key Features 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 Edge detection image erosin and morphing tools Opotex TIFF an dLispix RAW file importers Enables most standard PLS Toolbox functions to work with images System Requirements Requires PLS Toolbox and MATLAB 6 5 7 x or higher MIA Toolbox does not require other MATLAB toolboxes other than PLS Toolbox Like most MATLAB toolboxes MIA Toolbox is platform independent It will function on any platform on which MATLAB functions e g MAC PC Linux NOTE You must upgrade your PLS Toolbox to the corresponding latest version

    Original URL path: http://www.eigenvector.com/software/mia_toolbox.htm (2016-04-27)
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  • EMSC_Toolbox - Eigenvector Research, Inc.
    reflectance spectroscopy which is depended on particle size distributions EMSC expands on the popular Multiplicative Scatter Signal Correction technique by offering much improved flexibility in selecting backgrounds to subtract known interferences as well as scaling targets and known analyte spectra Examples of this leading edge technology Martens H Stark E Extended multiplicative signal correction and spectral interference subtraction new preprocessing methods for near infrared spectroscopy Journal of Pharmaceutical and Biomedical

    Original URL path: http://www.eigenvector.com/software/emsc_toolbox.htm (2016-04-27)
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  • Solo - Eigenvector Research, Inc.
    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 Solo provides the Graphical Interfaces to quickly manage and analyze data author and apply models and interpret results 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 System Requirements MAC OSX Intel Linux or Windows XP VISTA Win7 Win 8 250 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 Product Support Eigenvector Research offers user support for Solo by e mail at helpdesk eigenvector com Questions are almost always answered within 24 hours and usually much less Updates and bug fixes can be downloaded

    Original URL path: http://www.eigenvector.com/software/solo.htm (2016-04-27)
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  • Solo+MIA - Eigenvector Research, Inc.
    automatically present appropriate model results in image format Image importing and building functions to make assembly of multivariate images easier Image specific functions including Maximal Autocorrelation Factors MAF and an image enhanced Cluster analysis Enables most standard Solo analysis methods to work with images Includes all of these features and more Data Exploration and Pattern Recognition Principal Components Analysis Parallel Factor Analysis Regression Modeling Partial Least Squares Principal Components Regression Multiple Linear Regression Classification SIMCA PLS Discriminant Analysis Cluster Analysis with Dendograms Self modeling Curve Resolution Pure Variable Methods Multivariate Curve Resolution Purity compare to SIMPLSMA Instrument Standardization Piece wise Direct Generalized Least Squares Preprocessing Advanced Graphical Data Set Editing and Visualization Tools Advanced Customizable Order Specific Preprocessing Centering Scaling Smoothing Derivatizing plus many more Get More Information Download a fully functional 30 day demo Learn about our latest release View the Software User Guide on line View the License Maintenance Agreement System Requirements MAC OSX Intel Linux or Windows XP VISTA Win7 Win8 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 Product Support Eigenvector Research

    Original URL path: http://www.eigenvector.com/software/solo+mia.htm (2016-04-27)
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  • Solo_Predictor - Eigenvector Research, Inc.
    Supported by Solo Predictor All preprocessing methods available in the custom preprocessing interface of PLS Toolbox or Solo including mean centering autoscaling block scaling derivatives smoothing baselineing OSC SNV MSC EMSC normalization GLSW and more All standard PLS Toolbox and Solo model types supported including exploratory regression and classification models PCA PLS PCR CLS MLR SVM MCR MPCA SIMCA PLSDA SVMDA Purity KNN PARAFAC PARAFAC2 Tucker NPLS and more Instrument standardization developed in PLS Toolbox or Solo in the CalTransfer GUI Key Features Stand alone operation requires no additional software Flexible interfacing option including web based process monitor Scriptable through easy to use text commands Support of all standard model types Automatic application of preprocessing Automatic variable alignment and missing data replacement Trusted industry standard calculation engine System Requirements Windows XP VISTA Win7 Win8 or Intel Linux 250 MB of free disk space and a recommended minimum of 100 MB of RAM more may be necessary for some applications Networked operation requires a network card and infrastructure not required for local client operation Flexible Interfacing Options Solo Predictor offers a wide range of interfacing options to simplify connection to existing clients and data management systems Interfaces include ActiveX NET TCP IP sockets Timed action or a simple Wait for File mode Solo Predictor can be located on the same computer as a client application local operation or on a networked computer networked operation A single Solo Predictor server can also act as a prediction engine for more than one client Solo Predictor is also operating system independent and can provide web based reporting and control Product Support Eigenvector Research offers user support for Solo Predictor by e mail at helpdesk eigenvector com Questions are almost always answered within 24 hours and usually much less Updates and bug fixes will be

    Original URL path: http://www.eigenvector.com/software/solo_predictor.htm (2016-04-27)
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  • Model_Exporter - Eigenvector Research, Inc.
    compilable on Windows or Linux and as a NET binary Use these in your own code and distribute unlimited models in a wide range of applications Example Applications Handheld or embedded computation devices High throughput applications requiring high speed data manipulation and calculations Distributed applications in MathWorks MATLAB or Octave software On line predictions using Matlab LabView or Symbion Systems Symbion software Model Exporter allows you to be self sufficient and run all the calculations in your own environment Let Eigenvector Do the Math Don t reinvent the mathematical steps and translate complicated proprietary file formats Model Exporter will provide all the model parameters and numerical calculations you need to make a prediction for a wide range of models including PCA models regression models PLS PCR CLS SVM and ANN and classification models PLSDA and SVMC including all the preprocessing Generic XML format The XML output format can be parsed by the supplied C or Java interpreters or you can translate those engines for your own environment All you need to provide is the ability to parse XML manage matrices and do several simple mathematical operations Model Exporter handles everything else LabView MATLAB and Symbion applications Predictors exported to m file or tcl file formats can be used in LabView MATLAB or Symbion These predictors can be run without the need for any additional toolboxes or purchased libraries The MATLAB m file script will even run in the free Octave package and the Symbion scripts will run in free Tcl parsers Plug in modular design By using a modular self describing script format you can easily update models without the need to recompile your application Simply make a new XML m file or tcl file available to your program and the new model will automatically be used You need know

    Original URL path: http://www.eigenvector.com/software/model_exporter.htm (2016-04-27)
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