Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Response surface methodology (RSM) as a tool for optimization in analytical chemistry

Matrix Differential Calculus with Applications in Statistics and Econometrics

A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies.

Supervised pattern recognition in food analysis.

Data fusion methodologies for food and beverage authentication and quality assessment - a review.

Transfer of multivariate calibration models: a review

This paper gives an introduction to multivariate calibration from a chemometrics perspective and reviews the various proposals to generalize the well-established univariate methodology to the multivariate domain. Univariate calibration leads to relatively simple models with a sound statistical underpinning. The associated uncertainty estimation and figures of merit are thoroughly covered in several official documents. However, univariate model predictions for unknown samples are only reliable if the signal is sufficiently selective for the analyte of interest. By contrast, multivariate calibration methods may produce valid predictions also from highly unselective data. A case in point is quantification from near-infrared (NIR) spectra. With the ever-increasing sophistication of analytical instruments inevitably comes a suite of multivariate calibration methods, each with its own underlying assumptions and statistical properties. As a result, uncertainty estimation and figures of merit for multivariate calibration methods has become a subject of active research, especially in the field of chemometrics.

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Uncertainty estimation and figures of merit for multivariate calibration (IUPAC Technical Report)

Calculation of the reliability of classification in discriminant partial least-squares binary classification

Rapid detection of olive–pomace oil adulteration in extra virgin olive oils from the protected denomination of origin “Siurana” using excitation–emission fluorescence spectroscopy and three-way methods of analysis

Joan Ferré

Papers

Data fusion methodologies for food and beverage authentication and quality assessment - a review.

Transfer of multivariate calibration models: a review

Uncertainty estimation and figures of merit for multivariate calibration (IUPAC Technical Report)

Calculation of the reliability of classification in discriminant partial least-squares binary classification

Rapid detection of olive–pomace oil adulteration in extra virgin olive oils from the protected denomination of origin “Siurana” using excitation–emission fluorescence spectroscopy and three-way methods of analysis