Multivariate Analysis is an increasingly common tool in experimental high energy physics; however, many of the common approaches were borrowed from other fields. We clarify what the goal of a multivariate algorithm should be for the search for a new particle and compare different approaches. We also translate the Neyman-Pearson theory into the language of statistical learning theory.
@article{arxiv.physics/0310110,
title = {Multivariate Analysis from a Statistical Point of View},
author = {Kyle S. Cranmer},
journal= {arXiv preprint arXiv:physics/0310110},
year = {2014}
}
Comments
Talk from PhyStat2003, Stanford, Ca, USA, September 2003, 4 pages, LaTeX, 1 eps figures. PSN WEJT002