A decision theoretical approach to wavelet regression on curves with a high number of regressors

DOI10.1016/S0378-3758(02)00333-6zbMath1032.62004OpenAlexW2081091379MaRDI QIDQ1869117

T. Fearn, Marina Vannucci, Philip J. Brown

Publication date: 9 April 2003

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0378-3758(02)00333-6

zbMATH Keywords

Genetic algorithmsRegressionSimulated annealingWavelet transformsBayes methodsNear-infrared spectroscopy

Mathematics Subject Classification ID

Multivariate analysis (62H99) Bayesian problems; characterization of Bayes procedures (62C10) Numerical methods for wavelets (65T60)

Related Items (5)

A survey of Bayesian predictive methods for model assessment, selection and comparison ⋮ Multivariate denoising using wavelets and principal component analysis ⋮ Support vector machines for classification of aggregates by means of IR-spectra ⋮ Space‐time modelling of trends in temperature series ⋮ Genetic Algorithm in the Wavelet Domain for LargepSmallnRegression

Uses Software

• Algorithm 735
• PLS_Toolbox

Cites Work

• Principal component analysis.
• Some matrix-variate distribution theory: Notational considerations and a Bayesian application
• Ten Lectures on Wavelets
• Multiresolution Approximations and Wavelet Orthonormal Bases of L 2 (R)
• Multivariate Bayesian Variable Selection and Prediction
• Algorithm 735: Wavelet transform algorithms for finite-duration discrete-time signals
• Bayesian Wavelet Regression on Curves With Application to a Spectroscopic Calibration Problem
• The choice of variables in multivariate regression: a non-conjugate Bayesian decision theory approach
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