Title: A multiresolution approach to time warping achieved by a Bayesian prior-posterior transfer fitting strategy
Authors: Claeskens, Gerda ×
Silverman, Bernard
Slaets, Leen #
Issue Date: 2010
Publisher: Royal Statistical Society
Series Title: Journal of the Royal Statistical Society B, Statistical Methodology vol:72 issue:5 pages:673-694
Abstract: Warping is an approach to the reduction and analysis of phase variability in functional observations, by applying a smooth bijection to the function argument. We propose a natural representation of warping functions in terms of a new type of elementary functions named 'warping component functions', or 'warplets', which are combined into the warping function by composition. The inverse warping function is trivial and explicit to obtain. A sequential Bayesian estimation strategy is introduced which fits a series of models and transfers the posterior of the previous fit into the prior of the next fit. Model selection is based on a warping analogue to wavelet thresholding, combined with Bayesian inference.
ISSN: 1369-7412
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Center for Operations Research and Business Statistics (ORSTAT), Leuven
× corresponding author
# (joint) last author

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