A Wavelet- or Lifting-Scheme-Based Imputation Method

DOI10.1111/j.1467-9868.2007.00649.xOpenAlexW2095477599WikidataQ123375466 ScholiaQ123375466MaRDI QIDQ3631462

T. J. Heaton, Bernhard W. Silverman

Publication date: 10 June 2009

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9868.2007.00649.x

zbMATH Keywords

waveletskriginglifting schemethin plate splinesGibbs samplerimputationBayesian prior

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (3)

Multiscale Methods for Data on Graphs and Irregular Multidimensional Situations ⋮ Empirical stationary correlations for semi-supervised learning on graphs ⋮ COMPARISON OF DIFFERENT WAVELET TECHNIQUES FOR FINDING CHANGE POINTS

Uses Software

• fields

Cites Work

• Unnamed Item
• Inference from iterative simulation using multiple sequences
• Needles and straw in haystacks: Empirical Bayes estimates of possibly sparse sequences
• Empirical Bayes selection of wavelet thresholds
• Sampling-Based Approaches to Calculating Marginal Densities
• A theory for multiresolution signal decomposition: the wavelet representation
• Orthonormal bases of compactly supported wavelets
• Ten Lectures on Wavelets
• Multiresolution Approximations and Wavelet Orthonormal Bases of L 2 (R)
• Wavelet Thresholding via A Bayesian Approach
• The Lifting Scheme: A Construction of Second Generation Wavelets
• Statistics for Spatial Data

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