Multivariate Goodness of Fit Procedures for Unbinned Data: An Annotated Bibliography

Details Multivariate Goodness of Fit Procedures for Unbinned Data: An Annotated Bibliography Multivariate Goodness of Fit Procedures for Unbinned Data: An Annotated Bibliography

2011-02-11

arxiv.org/abs/1102.2407v1

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Unbinned maximum likelihood is a common procedure for parameter estimation. After parameters have been estimated, it is crucial to know whether the fit model adequately describes the experimental data. Univariate Goodness of Fit procedures have been thoroughly analyzed. In multi-dimensions, Goodness of Fit test powers have rarely been studied on realistic problems. There is no definitive answer to regarding which method is better. Test performance is strictly related to specific analysis characteristics. In this work, a review of multi-variate Goodness of Fit techniques is presented.

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