NEW SELECTION APPROACH FOR RESOLUTION AND BASIS FUNCTIONS IN WAVELET REGRESSION

DOI10.11568/KJM.2014.22.2.289zbMath1488.62051OpenAlexW2122691962MaRDI QIDQ5217518

Chun Gun Park

Publication date: 24 February 2020

Published in: Korean Journal of Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.11568/kjm.2014.22.2.289

zbMATH Keywords

Bayes factorwavelet basis functionswavelet regressionprimary resolutionpositerior model probability

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07) Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40)

Uses Software

• Wavelet Toolbox

Cites Work

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• Bayesian selection of primary resolution and wavelet bias functions for wavelet regression
• Nonparametric regression using Bayesian variable selection
• Nonparametric smoothing and lack-of-fit tests
• Empirical Bayes selection of wavelet thresholds
• Adapting to Unknown Smoothness via Wavelet Shrinkage
• A theory for multiresolution signal decomposition: the wavelet representation
• Ten Lectures on Wavelets
• Ideal spatial adaptation by wavelet shrinkage
• A Bayesian Approach to Nonparametric Bivariate Regression

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