Metrohm Vision – Theory - Manual (Page 6)

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4 Sample Selection Methods ........................................................................................... 18
4.1 Mahalanobis Distance in Principal Component Space ................................ 18
4.1.1 Outlier Detection .................................................................................................. 18
4.1.2 Redundant Samples Selection ............................................................................... 18
4.2 Maximum Distance in Wavelength Space ................................................... 19
4.2.1 Outlier Detection .................................................................................................. 19
4.2.2 Redundant Sample Selection................................................................................. 19
4.3 Random Selection ...................................................................................... 19
4.4 Sample Selection Based on Lab Data (Quantitative) ................................... 20
5 Identification and Qualification Methods ..................................................................... 21
5.1 Wavelength Correlation ............................................................................. 21
5.1.1 Model Development ............................................................................................. 21
5.1.2 Analysis of an Unknown ....................................................................................... 21
5.2 Wavelength Maximum Distance ................................................................. 21
5.2.1 Model Development ............................................................................................. 21
5.2.2 Analysis of an Unknown ....................................................................................... 21
5.3 Mahalanobis Distance in Principal Component Space ................................ 21
5.3.1 Model Development ............................................................................................. 21
5.3.2 Analysis of an Unknown ....................................................................................... 22
5.4 Residual Variance in Principal Component Space ....................................... 22
5.4.1 Model Development ............................................................................................. 22
5.4.2 Analysis of an Unknown ....................................................................................... 23
6 Library Clustering ........................................................................................................ 24
6.1 General Description .................................................................................... 24
6.2 The Minimal Spanning Tree Algorithm ....................................................... 24
6.3 Clustering Algorithm .................................................................................. 24
6.4 Analysis of an Unknown............................................................................. 25