Douglas N. Rutledge

发表

Identification of significant factors by an extension of ANOVA-PCA based on multi-block analysis

D. Jouan-Rimbaud Bouveresse, R. Climaco Pinto, Leigh Schmidtke, 2011 .

A comparison of PCA, ICA and common components analysis applied to volatolomic data

Douglas N. Rutledge, Jihéne Bouhlel, Jérémy Ratel, 2017 .

Proficiency testing schemes: solutions for homogeneity control

Douglas N. Rutledge, Marie E. Lafargue, Sandrine Biogeaud, 2004 .

Chapter 9 A windows program for relaxation parameter estimation

Douglas N. Rutledge, 1996 .

Independent components analysis with the JADE algorithm

D. Jouan-Rimbaud Bouveresse, Douglas N. Rutledge, D. Rutledge, 2012 .

Application of independent components analysis with the JADE algorithm and NIR hyperspectral imaging for revealing food adulteration

Jean-Michel Roger, Douglas N. Rutledge, Puneet Mishra, 2016 .

Potential of the FT-ICR instrument equipped with dynamically harmonized cell, to perform high throughput metabolomic analyse.

Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse, Baninia Habchi, 2017 .

Segmented principal component transform–principal component analysis

Douglas N. Rutledge, António S. Barros, D. Rutledge, 2005 .

Polar coordinates projection: A simple data visualization tool

Douglas N. Rutledge, Delphine Bouveresse, Christophe Malabat, 2005 .

Utilising variable sorting for normalisation to correct illumination effects in close-range spectral images of potato plants

Douglas N. Rutledge, Gerrit Polder, Aoife A. Gowen, 2020 .

Principal components transform-partial least squares: a novel method to accelerate cross-validation in PLS regression

Douglas N. Rutledge, António S. Barros, D. Rutledge, 2004 .

Can we trust untargeted metabolomics? Results of the metabo-ring initiative, a large-scale, multi-instrument inter-laboratory study

Douglas N. Rutledge, Jean-Philippe Antignac, Delphine Jouan-Rimbaud Bouveresse, 2014, Metabolomics.

New data preprocessing trends based on ensemble of multiple preprocessing techniques

Jean-Michel Roger, Federico Marini, Douglas N. Rutledge, 2020 .

Independent Components Analysis: Theory and Applications

D. Jouan-Rimbaud Bouveresse, Douglas N. Rutledge, D. Rutledge, 2016 .

A variable selection method for multiclass classification problems using two-class ROC analysis

Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse, Christophe B.Y. Cordella, 2018, Chemometrics and Intelligent Laboratory Systems.

PLS_Cluster: a novel technique for cluster analysis

Douglas N. Rutledge, António S. Barros, 2004 .

ComDim Methods for the Analysis of Multiblock Data in a Data Fusion Perspective

Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse, Véronique Cariou, 2019, Data Handling in Science and Technology.

Robustness of models developed by multivariate calibration. Part I: The assessment of robustness

Véronique Bellon-Maurel, Douglas N. Rutledge, Jean-Michel Roger, 2004 .

Source inference of ignitable liquids in forensic science: an untargeted chemometric approach

Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse, Christophe B.Y. Cordella, 2018 .

Use of the common components and specific weights analysis to interpret supersaturated designs

Douglas N. Rutledge, M. Claeys-Bruno, Michelle Sergent, 2016 .

Can we trust untargeted metabolomics: results of the metabo-ring study

Douglas N. Rutledge, Jean-Philippe Antignac, Delphine Jouan-Rimbaud Bouveresse, 2012 .

Corrigendum to ‘Independent Components Analysis with the JADE algorithm’

D. Jouan-Rimbaud Bouveresse, Douglas N. Rutledge, 2015 .

A comprehensive approach to method validation based on object technology

Douglas N. Rutledge, Max Feinberg, Alice Gerbanowski, 1997 .

FRUITNIR-GUI: A graphical user interface for correcting external influences in multi-batch near infrared experiments related to fruit quality prediction

Jean-Michel Roger, Federico Marini, Douglas N. Rutledge, 2020 .

Modelling of statistical tables for outlier tests

Douglas N. Rutledge, Emmanuel Bugner, 1990 .

ComDim: From multiblock data analysis to path modeling

Douglas N. Rutledge, Evelyne Vigneau, Véronique Cariou, 2017, Food Quality and Preference.

A short note on achieving similar performance to deep learning with practical chemometrics

Douglas N. Rutledge, Jean-Michel Roger, Puneet Mishra, 2021, Chemometrics and Intelligent Laboratory Systems.

A generic workflow combining deep learning and chemometrics for processing close-range spectral images to detect drought stress in Arabidopsis thaliana to support digital phenotyping

Gerrit Polder, Douglas N. Rutledge, Maxime Ryckewaert, 2021 .

Monte Carlo methods for estimating Mallows's Cp and AIC criteria for PLSR models. Illustration on agronomic spectroscopic NIR data

Douglas N. Rutledge, Matthieu Lesnoff, Jean‐Michel Roger, 2021, Journal of Chemometrics.

Rearrangement of incomplete multi-omics datasets combined with ComDim for evaluating replicate cross-platform variability and batch influence

Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse, Olivier Chapleur, 2021, Chemometrics and Intelligent Laboratory Systems.

Complementary chemometrics and deep learning for semantic segmentation of tall and wide visible and near-infrared spectral images of plants

Gerrit Polder, Douglas N. Rutledge, Puneet Mishra, 2021, Comput. Electron. Agric..

Discriminability and uncertainty in principal component analysis (PCA) of temporal check-all-that-apply (TCATA) data

Tormod Næs, Douglas N. Rutledge, John C. Castura, 2021 .

Digital images and independent components analysis in the determination of bioactive compounds from grape juice

Douglas N. Rutledge, Patrícia Valderrama, Paulo Henrique Março, 2021 .

Are standard sample measurements still needed to transfer multivariate calibration models between near-infrared spectrometers? The answer is not always

Douglas N. Rutledge, Alessandra Biancolillo, Jean-Michel Roger, 2021 .

Detecting information in gas sensor responses using analysis of variance

Gilles Trystram, Douglas N. Rutledge, António S. Barros, 1998 .

PoLiSh — smoothed partial least-squares regression

Douglas N. Rutledge, António S. Barros, Ivonne Delgadillo, 2001 .

Fruit juice authentication by 1H NMR spectroscopy in combination with different chemometrics tools

Douglas N. Rutledge, Ian J. Colquhoun, Michèle Lees, 2008, Analytical and bioanalytical chemistry.

Independent components analysis as a means to have initial estimates for multivariate curve resolution-alternating least squares

Douglas N. Rutledge, Patrícia Valderrama, Paulo Henrique Março, 2016 .

Rare and Low Frequency Variant Stratification in the UK Population: Description and Impact on Association Tests

Douglas N. Rutledge, Marie-Claude Babron, Eleftheria Zeggini, 2012, PloS one.

Analysis of Time Domain NMR and Other Signals

Douglas N. Rutledge, António S. Barros, M. C. Vackier, 1999 .

Two novel methods for the determination of the number of components in independent components analysis models

D. Jouan-Rimbaud Bouveresse, Douglas N. Rutledge, A. Moya-González, 2012 .

SPORT pre-processing can improve near-infrared quality prediction models for fresh fruits and agro-materials

Douglas N. Rutledge, Puneet Mishra, Ernst Woltering, 2020 .

A case study of extrapolation in NIR modelling — A chemometric challenge at ‘Chimiométrie 2009’

Douglas N. Rutledge, Vincent Baeten, Pierre Dardenne, 2011 .

MBA-GUI: A chemometric graphical user interface for multi-block data visualisation, regression, classification, variable selection and automated pre-processing

Douglas N. Rutledge, Alessandra Biancolillo, Federico Marini, 2020, Chemometrics and Intelligent Laboratory Systems.

GENETIC ALGORITHM APPLIED TO THE SELECTION OF PRINCIPAL COMPONENTS

Douglas N. Rutledge, António S. Barros, D. Rutledge, 1998 .

Correlation between sensory data, instrumental data (gas sensors, physico-chemical analysis) and palatability measurements of 12 moist foods for cats

Gilles Trystram, Douglas N. Rutledge, J. Hossenlopp, 1999 .

Determination of the degree of methylesterification of pectic polysaccharides by FT-IR using an outer product PLS1 regression

Douglas N. Rutledge, António S. Barros, Ivonne Delgadillo, 2002 .

An evaluation of the PoLiSh smoothed regression and the Monte Carlo Cross-Validation for the determination of the complexity of a PLS model

Douglas N. Rutledge, Desire L. Massart, Susan Gourvenec, 2003 .

Improving the detection of significant factors using ANOVA-PCA by selective reduction of residual variability.

Douglas N. Rutledge, Leigh M. Schmidtke, António S. Barros, 2009, Analytica chimica acta.

Independent components analysis applied to 3D-front-face fluorescence spectra of edible oils to study the antioxidant effect of Nigella sativa L. extract on the thermal stability of heated oils

Douglas N. Rutledge, Christophe B.Y. Cordella, D. Rutledge, 2012 .

Durbin–Watson statistic as a morphological estimator of information content

Douglas N. Rutledge, António S. Barros, 2002 .

Relations between Mid-Infrared and Near-Infrared Spectra Detected by Analysis of Variance of an Intervariable Data Matrix

Douglas N. Rutledge, Marie-Françoise Devaux, António S. Barros, 1997 .

Automatic de-noising of close-range hyperspectral images with a wavelength-specific shearlet-based image noise reduction method

Douglas N. Rutledge, Jean-Michel Roger, Alison Nordon, 2019, Sensors and Actuators B: Chemical.

Detection of Heterogeneous Wheat Samples Using near Infrared Spectroscopy

Douglas N. Rutledge, Jean-Jacques Daudin, Marie E. Lafargue, 2003 .

FTIR spectroscopy as a tool for the analysis of olive pulp cell-wall polysaccharide extracts

Douglas N. Rutledge, António S. Barros, Ivonne Delgadillo, 1999 .

Two standard-free approaches to correct for external influences on near-infrared spectra to make models widely applicable

Douglas N. Rutledge, Puneet Mishra, Ernst Woltering, 2020 .

Multivariate statistical analysis of two-dimensional NMR data to differentiate grapevine cultivars and clones

Douglas N. Rutledge, D. Rutledge, J. Vercauteren, 1996 .

ANOVA and factor analysis applied to time domain NMR signals

Douglas N. Rutledge, António S. Barros, F. Gaudard, 1997 .