Journal of Statistical Software (Oct 2013)

Warping Functional Data in R and C via a Bayesian Multiresolution Approach

  • Leen Slaets,
  • Gerda Claeskens,
  • Bernard W. Silverman

DOI
https://doi.org/10.18637/jss.v055.i03
Journal volume & issue
Vol. 55, no. 1
pp. 1 – 22

Abstract

Read online

Phase variation in functional data obscures the true amplitude variation when a typical cross-sectional analysis of these responses would be performed. Time warping or curve registration aims at eliminating the phase variation, typically by applying transformations, the warping functions ?n, to the function arguments. We propose a warping method that jointly estimates a decomposition of the warping function in warping components, and amplitude components. For the estimation routine, adaptive MCMC calculations are performed and implemented in C rather than R to increase computational speed. The R-C interface makes the program user-friendly, in that no knowledge of C is required and all input and output will be handled through R. The R package MRwarping contains all needed files.