A Statistical View of Some Chemometrics Regression Tools

Keywords

Chemometrics, Partial least squares regression, Principal component regression, Computer science, Statistics

References

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• The Bayesian estimation of common parameters from several responsesGeorge E. P. Box, Norman R. Draper — 1965
• A Critique of Some Ridge Regression MethodsGary Smith, Frank W. Campbell — 1980
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• Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear EstimationDonald W. Marquardt — 1970
• Continuum regression: Cross-validated sequentially constructed prediction embracing ordinary least sM. Stone, Randall Brooks — 1990
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• A UNIVERSAL PRIOR FOR INTEGERS AND ESTIMATION BY MINIMUM DESCRIPTION LENGTHJ. Rissanen — 1983
• Cross‐Validatory Choice and Assessment of Statistical PredictionsM. Stone — 1976
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• Smoothing noisy data with spline functionsGrace Wahba — 1975
• Estimating the Dimension of a ModelGideon Schwarz — 1978
• ON THE STRUCTURE OF PARTIAL LEAST SQUARES REGRESSIONInge S. Helland — 1988
• The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized InversesSvante Wold, Axel Ruhe, Herman Wold — 1984
• On the Investigation of Alternative Regressions by Principal Component AnalysisDouglas M. Hawkins — 1973

Cited by

• Some perspectives of smooth and locally sparse estimatorsZhenhua Lin — 2013
• A Comparison Study of Principle Component Regression, Partial Least Square Regression and Ridge Regression with Application to FTIR DataYing Li — 2010
• Significance Regression: A Statistical Approach to Biased Linear Regression and Partial Least SquaresTyler R. Holcomb, Håkan Hjalmarsson, Manfred Morari — 1993
• Réduction de dimension dans les modèles linéaires généralisés : Application à la classification supervisée de données issues des biopucesGersende Fort, Sophie Lambert‐Lacroix, Julie Peyre — 2005
• Classification and prediction in pharmacogenetics--context, construction and validation.Elizabeth Griffin — 2002
• A Formulation Development Strategy for Multivariate Kinetic ResponsesSigit Sudjatmiko — 2002
• Régression sur variable fonctionnelle : estimation, tests de structure et applicationsLaurent Delsol — 2008
• From Multivariate to Functional Linear RegressionLuboš Prchal — 2005
• Penalized Discriminant Methods for the Classification of Tumors from Gene Expression DataDebashis Ghosh — 2003
• Spatially Aggregated Multi-Class Pattern Classification in Functional MRI using Optimally Selected Functional Brain Areas志行 秩父 — 2012
• Partial Least Square Regression PLS-RegressionHervé Abdi — 2007
• Locally Adaptive Smoothing with Markov Random Fields and Shrinkage PriorsИлья Затковецкий, Сергей Георгиевич Шульгин, Константин Эдуардович Яновский — 2015
• Inverting hyperspectral images with Gaussian Regularized Sliced Inverse RegressionCaroline Bernard-Michel, Laurent Gardès — 2008
• Nonconvex selection in nonparametric additive modelsXiangmin Zhang, Dale Zimmerman, Jian Huang — 2014
• Can indices of landscape function analysis (LFA) be derived from ground-based spectroscopy? A case study from gold mines on the Highveld of South AfricaDavid Furniss — 2009
• A Connection Between Variable Selection and EM-Type AlgorithmsDavid R. Hunter, Runze Li — 2002
• Model selection and estimation in additive regression modelsHuiping Miao — 2009
• Shape Distinction for 3D Object RetrievalPhilip Shilane — 2008
• A comparison of multivariate calibration techniques applied to experimental NIR data sets: Part II. Predictive ability under extrapolation conditionsFrédéric Estienne, Luisa Pasti, V. Centner — 2001
• Quelques contributions à la sélection de variables et aux tests non-paramétriquesLaëtitia Comminges — 2012

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