Estimation of Goodness-of-Fit in Multidimensional Analysis Using Distance to Nearest Neighbor

Details Estimation of Goodness-of-Fit in Multidimensional Analysis Using Distance to Nearest Neighbor Estimation of Goodness-of-Fit in Multidimensional Analysis Using Distance to Nearest Neighbor

2003-06-24

arxiv.org/abs/physics/0306171v1

Physics

Data Analysis, Statistics and Probability

15 pages, 8 figures, 1 table

Scientific paper

A new method for calculation of goodness of multidimensional fits in particle physics experiments is proposed. This method finds the smallest and largest clusters of nearest neighbors for observed data points. The cluster size is used to estimate the goodness-of-fit and the cluster location provides clues about possible problems with data modeling. The performance of the new method is compared to that of the likelihood method and Kolmogorov-Smirnov test using toy Monte Carlo studies. The new method is applied to estimate the goodness-of-fit in a B->Kll analysis at BaBar.

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