A nonparametric resampling procedure is proposed to test the significance of a mode, with the aim of evaluating whether a region of relatively high observed density reflects the actual presence of a mode in the true distribution underlying a set of data. The method leverages on Morse theory and stochastic gradient methods to characterize the local properties of the modes. This allows the definition of an asymptotic test, based on the concept of gradient ascent paths and relying on resampling methods, to approximate the distribution of the test statistic under the null hypothesis.

Nonparametric test for density modes

Ferraccioli Federico;Menardi Giovanna
2022-01-01

Abstract

A nonparametric resampling procedure is proposed to test the significance of a mode, with the aim of evaluating whether a region of relatively high observed density reflects the actual presence of a mode in the true distribution underlying a set of data. The method leverages on Morse theory and stochastic gradient methods to characterize the local properties of the modes. This allows the definition of an asymptotic test, based on the concept of gradient ascent paths and relying on resampling methods, to approximate the distribution of the test statistic under the null hypothesis.
2022
Proceedings in 16th International Conference on Computational and Financial Econometrics (CFE 2022) and 15th International Conference of the ERCIM (European Research Consortium for Informatics and Mathematics) Working Group on Computational and Methodological Statistics (CMStatistics 2022)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5082729
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