This is the companion package of a PhD thesis entitled "Bases Giving Distances. A new paradigm for investigating functional data with applications for spectroscopy" by Timmermans (2012). See references for details and related publications. The core of the BAGIDIS methodology is a functional wavelet based semidistance that has been introduced by Timmermans and von Sachs (2010, 2015) and Timmermans, Delsol and von Sachs (2013). This semidistance allows for comparing curves with sharp local patterns that might not be well aligned from one curve to another. It is datadriven and highly adaptive to the curves being studied. Its main originality is its ability to consider simultaneously horizontal and vertical variations of patterns, which proofs highly useful when used together with clustering algorithms or visualization method. BAGIDIS is an acronym for BAsis GIving DIStances. The extension of BAGIDIS to image data relies on the same principles and has been described in Timmermans and Fryzlewicz (2012), Fryzlewicz and Timmermans (2015).
Package details 


Author  Catherine Timmermans 
Maintainer  Catherine Timmermans <[email protected]> 
License  GPL 
Version  1.0 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.