Published March 2007 | Version v1
Journal article

Multivariate analysis methods in physics

Creators

  • 1. Henryk Niewodniczański Institute of Nuclear Physics, Polish Academy of Sciences, Krakow (Poland)

Description

In this article, a review of multivariate methods based on statistical learning is given. Several popular multivariate methods useful in high-energy physics analysis are discussed. Selected examples from current research in particle physics are discussed, both from online trigger selection and from off-line analysis. In addition, statistical learning methods, not yet applied in particle physics, are presented and some new applications are suggested.

Availability note (English)

Available from http://link.springer.com/openurl/pdf?id=doi:10.1134/S1063779607020050

Additional details

Publishing Information

Journal Title
Physics of Particles and Nuclei
Journal Volume
38
Journal Issue
2
Journal Page Range
p. 255-268
ISSN
1063-7796

INIS

Country of Publication
United States
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52014873
Subject category
S46: INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; S72: PHYSICS OF ELEMENTARY PARTICLES AND FIELDS;
Descriptors DEI
HIGH ENERGY PHYSICS; MULTIVARIATE ANALYSIS; PARTICLES
Descriptors DEC
MATHEMATICS; PHYSICS; STATISTICS

Optional Information

Copyright
Copyright (c) 2007 Pleiades Publishing, Ltd.