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Chemometrics Methods Development

Representation of multivariate model using TinyLVR

We have a long-standing interest in the application of chemometrics methods to high-dimensional (often spectral) datasets.

Recent work has focused on methods for assisting in the interpretation and visualization of the results of statistical analyses, such as "IFRNOPLS" (IFR's Non-Orthogonalized Partial Least Squares regression toolbox) and "TinyLVR" (tiny latent vector regression).


  • Tapp H. S., Penfold R. A., Kemsley E. K.(2011) Tinylvr: a utility for viewing single predictor multivariate models in terms of a two factor latent vector model Chemometrics and Intelligent Laboratory Systems 105 19-26 [doi:10.1016/j.chemolab.2010.10.006]
  • Tapp H. S., Kemsley E. K.(2009) Notes on the practical utility of OPLS Trends in Analytical Chemistry 28 1322-1327
  • Kemsley E. K., Tapp H. S.(2009) OPLS filtered data can be obtained directly from non-orthogonalized PLS1 Journal of Chemometrics 23 263-264
  • Tapp H. S., Kemsley E. K.(2008) Optimizing the efficiency of cross-validation in linear discriminant analysis through selective use of the Sherman-Morrison-Woodbury inversion formula Journal of Chemometrics 22 419-421
  • Kemsley E. K.(2001) A hybrid classification method: discrete canonical variate analysis using a genetic algorithm Chemometrics and Intelligent Laboratory Systems 55 39-51
  • Defernez M., Kemsley E. K.(1999) Avoiding overfitting in the analysis of high-dimensional data with artificial neural networks (ANNs). The Analyst 124 1675-1681
  • Tapp H. S., Kemsley E. K., Wilson R. H., Holley M. L.(1998) Image improvement in soft-field tomography through the use of chemometrics. Measurements in Science Technology 9 592-598
  • Kemsley E. K.(1998) A genetic algorithm (GA) approach to the calculation of canonical variates (CVs). Trends in Analytical Chemistry 17 24-34
  • Defernez M., Kemsley E. K.(1997) The use and misuse of chemometrics for treating classification problems. Trends in Analytical Chemistry 16 216-221
  • Kemsley E. K.(1996) Discriminant analysis of high-dimensional data: a comparison of principal components analysis and partial least squares data reduction methods Chemometrics and Intelligent Laboratory Systems 33 47-61


Funding: Our work on methods development has been supported by:

  • BBSRC Competitive Strategic Grant (2000 - present)
  • MAFF (1997 - 1999)