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/S1063779607020050Additional details
Identifiers
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.