Testing Serial Independence via Density-Based Measures of Divergence

Luca Bagnato (), Lucio De Capitani () and Antonio Punzo ()
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Luca Bagnato: Università Cattolica del Sacro Cuore
Lucio De Capitani: Università di Milano-Bicocca
Antonio Punzo: Università di Catania

Methodology and Computing in Applied Probability, 2014, vol. 16, issue 3, 627-641

Abstract: Abstract This article reviews some nonparametric serial independence tests based on measures of divergence between densities. Among others, the well-known Kullback–Leibler, Hellinger, Tsallis, and Rosenblatt divergences are analyzed. Moreover, their copula-based version is taken into account. Via a wide simulation study, the performances of the considered serial independence tests are compared under different settings. Both single-lag and multiple-lag testing procedures are investigated to find out the best “omnibus” solution.

Keywords: Serial independence; Divergence measures; Nonparametric density estimation; Copulas; Permutation tests; Multiple tests; 37M10; 62G10; 62F03; 62M10; 62G07; 62F40 (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s11009-013-9320-4

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