Statistical Analysis Techniques in Particle Physics Fits, Density Estimation and Supervised Learning
Statistical Analysis Techniques in Particle Physics Fits, Density Estimation and Supervised Learning
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Statistical Analysis Techniques in Particle Physics
Fits, Density Estimation and Supervised Learning
Ilya Narsky | Frank C. Porter
Science / Physics / Nuclear
Modern analysis of HEP data needs advanced statistical tools to separate signal from background. This is the first book which focuses on machine learning techniques. It will be of interest to almost every high energy physicist, and, due to its coverage, suitable for students.
The authors are experts in the use of statistics in particle physics data analysis. Frank C. Porter is Professor at Physics at the California Institute of Technology and has lectured extensively at CalTech, the SLAC Laboratory at Stanford, and elsewhere. Ilya Narsky is Senior Matlab Developer at The MathWorks, a leading developer of technical computing software for engineers and scientists, and the initiator of the StatPatternRecognition, a C++ package for statistical analysis of HEP data. Together, they have taught courses for graduate students and postdocs.
| Publication Date: | 31 December 2013 |
| Publisher: | Wiley |
| Imprint: | Wiley-VCH |
| ISBN-13: | 9783527410866 |
| Format: | Paperback softback |
| Page Count: | 459 |
| Weight (oz): | 34.56 |