MRwarp-package: This package performs Bayesian multiresolution time warping...
In MRwarping: Multiresolution time warping for functional data.

Description Details Author(s) References

Time warping is performed via a composition of warplets. The Bayesian model starts with one warplet and adds warplets one at a time until the warping action becomes negligible in the sense of having almost zero intensity or too narrow domains. The posterior distributions are used as prior distributions for the extended model in the next step. Warplets have an immediate interpretation as warping functions and the inverse warplet is trivial to obtain.

Package:	MRwarping
Type:	Package
Version:	1.0
Date:	2012-10-22
License:	What license is it under?
LazyLoad:	yes

L. Slaets, G. Claeskens, B.W. Silverman

Maintainer: <Gerda.Claeskens@kuleuven.be>

Slaets, Claeskens and Silverman (2010). Warping functional data in R and C via a Bayesian Multiresolution approach. Journal of Statistical Software, 55(3), 1-22,
URL http://www.jstatsoft.org/v55/i03/.

Claeskens, Silverman and Slaets (2010). A multiresolution approach to time warping achievec by a Bayesian prior-posterior transfer fitting strategy. Journal of the Royal Statistical Society, Series B, 72(5), 673-694.

MRwarping documentation built on May 2, 2019, 2:13 a.m.