Open AccessSYMMETRIC NONLINEAR REGRESSION
Author(s) -
Antal Tamás
Publication year - 2007
Publication title -
ets research report series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.235
H-Index - 5
ISSN - 2330-8516
DOI - 10.1002/j.2333-8504.2007.tb02055.x
Subject(s) - univariate , affine transformation , mathematics , computation , nonlinear system , set (abstract data type) , nonlinear regression , line (geometry) , regression , regression analysis , algebra over a field , pure mathematics , statistics , multivariate statistics , algorithm , computer science , geometry , physics , quantum mechanics , programming language
An estimation tool for symmetric univariate nonlinear regression is presented. The method is based on introducing a nontrivial set of affine coordinates for diffeomorphisms of the real line. The main ingredient making the computations possible is the Connes‐Moscovici Hopf algebra of these affine coordinates.