Convergence in total variation on Wiener chaos

Ivan Nourdin and Guillaume Poly

Stochastic Processes and their Applications, 2013, vol. 123, issue 2, 651-674

Abstract: Let {Fn} be a sequence of random variables belonging to a finite sum of Wiener chaoses. Assume further that it converges in distribution towards F∞ satisfying V ar(F∞)>0. Our first result is a sequential version of a theorem by Shigekawa (1980) [23]. More precisely, we prove, without additional assumptions, that the sequence {Fn} actually converges in total variation and that the law of F∞ is absolutely continuous. We give an application to discrete non-Gaussian chaoses. In a second part, we assume that each Fn has more specifically the form of a multiple Wiener–Itô integral (of a fixed order) and that it converges in L2(Ω) towards F∞. We then give an upper bound for the distance in total variation between the laws of Fn and F∞. As such, we recover an inequality due to Davydov and Martynova (1987) [5]; our rate is weaker compared to Davydov and Martynova (1987) [5] (by a power of 1/2), but the advantage is that our proof is not only sketched as in Davydov and Martynova (1987) [5]. Finally, in a third part we show that the convergence in the celebrated Peccati–Tudor theorem actually holds in the total variation topology.

Keywords: Convergence in distribution; Convergence in total variation; Malliavin calculus; Multiple Wiener–Itô integral; Wiener chaos (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (8)

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DOI: 10.1016/j.spa.2012.10.004

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