Gaussian lower bounds for the density via Malliavin calculus
Nguyen Tien Dung
TL;DR
This paper introduces a new representation for the density of Malliavin differentiable random variables, enabling the derivation of Gaussian lower bounds using a straightforward approach based on a known formula.
Contribution
The paper presents a novel, simplified method for obtaining lower bounds on the density of Malliavin differentiable variables, improving upon existing techniques.
Findings
Derived a new density representation formula
Established Gaussian lower bounds for densities
Simplified the process for density estimation
Abstract
In this paper, based on a known formula, we use a simple idea to get a new representation for the density of Malliavin differentiable random variables. This new representation is particularly useful for finding lower bounds for the density.
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Statistical Mechanics and Entropy · Random Matrices and Applications