A random model for multidimensional fitting method
Methodology
2018-10-12 v1
Abstract
Multidimensional fitting (MDF) method is a multivariate data analysis method recently developed and based on the fitting of distances. Two matrices are available: one contains the coordinates of the points and the second contains the distances between the same points. The idea of MDF is to modify the coordinates through modification vectors in order to fit the new distances calculated on the modified coordinates to the given distances. In the previous works, the modification vectors are taken as deterministic variables, so here we want to take into account the random effects that can be produce during the modification. An application in the sensometric domain is also given.
Cite
@article{arxiv.1810.05042,
title = {A random model for multidimensional fitting method},
author = {Hiba Alawieh and Frédéric Bertrand and Myriam Maumy-Bertrand and Nicolas Wicker and Baydaa Al Ayoubi},
journal= {arXiv preprint arXiv:1810.05042},
year = {2018}
}
Comments
30 pages, 5 figures