PLSplus IQ Prediction Reports
The PLSplus IQ Prediction Reports Setup allows you to specify how a spectrum is analysed and how to output the results each time you execute a calibration. Users can predict samples against multiple calibrations to determine if the spectrum matches the calibration well enough to give an accurate prediction.
Qualitative tests can be performed using quantitative models as if the calibrations were designed for that purpose. Using Discriminant Analysis as a prefilter before applying quantitative calculations allows PLSplus/IQ to select the calibration that best matches the sample spectrum. In addition, outlier samples can be quickly and easily determined during sample prediction giving you the utmost assurance of the results.
You can customise the prediction report to include constituent quantities, Mahalanobis Distance, Model Limits Tests, and spectral residual. Users can organise the report by constituent, calibration or sample and print, copy, or save the report to an ASCII file.
Each copy of PLSplus/IQ includes three additional licences for distributing your calibration model to other GRAMS/AI computer systems. In addition, many instrument systems can use the calibration directly.
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When working with many data points, graphing is often the quickest way to qualify data and identify trends. With the Origin statistics gadget, it’s also easy to pull quantitative information, such as mean and standard deviation, straight from a data plot. This lets me make better decisions about which data to select for more detailed analysis.Boaz Vilozny - Postdoctoral Researcher, University of California at Santa Cruz
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