Partial Least Squares regression, or Projection to Latent Structures, is a popular statistical method. It is used to predict any hidden information directly from the measured raw data. PLSR is often called soft modeling as well and can be applied to X-ray diffraction data (crystallinity, temperature, chemistry).
No further data processing is required and no knowledge of phases and structures is needed. The simulation of instrument influences is not necessary as long as they are kept constant. It is a perfect tool for cases where the number of variables is high, and where it is likely that the explanatory variables are correlated. Standards to calibrate a model are necessary. After the calibration the model can be used to predict the calibrated property from unknown samples. This method is an easy-to-use and accurate tool for determination of a single parameter.
Learn during the webinar how PLSR can be used for quantitative analysis of all types of additions in blended cements. This webinar will include a live question and answer session for our attendees.
No further data processing is required and no knowledge of phases and structures is needed. The simulation of instrument influences is not necessary as long as they are kept constant. It is a perfect tool for cases where the number of variables is high, and where it is likely that the explanatory variables are correlated. Standards to calibrate a model are necessary. After the calibration the model can be used to predict the calibrated property from unknown samples. This method is an easy-to-use and accurate tool for determination of a single parameter.
Learn during the webinar how PLSR can be used for quantitative analysis of all types of additions in blended cements. This webinar will include a live question and answer session for our attendees.
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Webinar details
Panelist: Thomas Fuellmann, Application Specialist XRD, PANalytical B.V., the Netherlands.