Advanced Preprocessing

Course Description

The objective of data preprocessing is to remove extraneous variance and anomalies and is often the critical step in development of a successful multivariate calibration or classification scheme. Advanced Preprocessing starts with a brief review of basic preprocessing then delves into more advanced topics such as multiplicative scatter correction, extended multiplicative scatter correction, and generalized least squares-like weighting. The objectives of preprocessing with respect to modeling are considered, along with the potential for creating artifacts and how to minimize them. The course includes hands-on computer time for participants to work example problems using PLS_Toolbox, EMSC_Toolbox, and MATLAB.

Prerequisites

MATLAB for Chemometricians and Chemometrics II--Regression and PLS or equivalent experience.

Course Outline

1. Matrix Rank and the Bilinear Model
   
2. Preprocessing Objectives
   
3. Mean- and Median-centering, Autoscaling
   
4. Normalization and Standard Normal Variate Scaling
   
5. Scaling for Multi-block data
   
6. Savitsky-Golay and Filtering
   
7. Orthogonal Signal Correction
   
8. Generalized Least Squares Weighting
   
9. Multiplicative Scatter Correction
   
10. Extended Multiplicative Scatter Correction