Project Description

New and innovative algorithms and methods of data analysis for nuclear physics experiments were proposed and published by Nikolay Gagunashvili (University of Iceland). These algorithms and methods need to be implemented as software programs to be used to analyze data collected by the high energy physics experiments. Thus, implementation of these algorithms and methods for the ROOT framework is the main goal of this project. Weighted histograms are used for the estimation of probability density functions. The bin content of a weighted histogram can be considered as a random sum of random variables that permits to generalize the classical Pearson’s goodness of fit test for histograms with weighted entries.

Tasks

• Development and implementation of C++ codes for goodness of fit tests for weighted histograms and integrate it in the ROOT Mathematical and Statistical libraries
• Development of tutorials and reference and users documentation

Requirements

Strong knowledge of C++11; being able to produce clean, reliable code; knowledge of basic statistics and numerical computation.

Mentors

• Nikolay Gagunashvili
• Lorenzo Moneta

Links

• ROOT
• N. Gagunashvili, Chi-square goodness of fit tests for weighted histograms. Review and Improvements, Journal of Instrumentation 10, (2015) P05004.

Corresponding Project

• ROOT

Participating Organizations

• CERN
• icelanduniversity

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