arXiv subjects

R. L. Schilling

Publications and source records attributed to R. L. Schilling.

4 recordsLinked to original sources

arXiv2026

Invariant Measures of Lévy-driven Stochastic Differential Equations

We study the structure and regularity of (infinitesimally) invariant measures of the solutions to stochastic differential equations $dX_t = b(X_t)\,dt + dZ_t$, where $(Z_t)_{t\geq 0}$ is a Lévy process. We show, in particular, that the invariant measure has to satisfy a Volterra-type convolution equation; since we can obtain the kernels explicitly, we are able to apply regularity methods from harmonic analysis. As an application, we get a very short proof -- in any dimension -- of a classic result due to Sato and Yamazato on the form of the invariant measure of a generalized Ornstein--Uhlenbeck process.

math.PR↗

arXiv2014

A note on the existence of transition probability densities for Lévy processes

We prove several necessary and sufficient conditions for the existence of (smooth) transition probability densities for Lévy processes and isotropic Lévy processes. Under some mild conditions on the characteristic exponent we calculate the asymptotic behaviour of the transition density as $t\to 0$ and $t\to\infty$ and show a ratio-limit theorem.

math.PR↗

arXiv2012

An Inequality Related to Negative Definite Functions

This is a substantially generalized version of the preprint arXiv:1105.4214 by Lifshits and Tyurin. We prove that for any pair of i.i.d. random vectors $X, Y$ in $R^n$ and any real-valued continuous negative definite function $g: R^n\to R$ the inequality $$ E g(X-Y) \le E g(X+Y)$$ holds. In particular, for $a \in (0,2]$ and the Euclidean norm $|.|$ one has $$ E |X-Y|^a \le E |X+Y|^a. $$ The latter inequality is due to A. Buja et al. (Ann. Statist., 1994} where it is used for some applications in multivariate statistics. We show a surprising connection with bifractional Brownian motion and provide some related counter-examples.

math.PR↗

arXiv2011

A geometric interpretation of the transition density of a symmetric Lévy Process

We study for a class of symmetric Lévy processes with state space $\rn$ the transition density $p_t(x)$ in terms of two one-parameter families of metrics, $(d_t)_{t>0}$ and $(δ_t)_{t>0}$. The first family of metrics describes the diagonal term $p_t(0)$; it is induced by the characteristic exponent $ψ$ of the Lévy process by $d_t(x,y)=\sqrt{tψ(x-y)}$. The second and new family of metrics $δ_t$ relates to $\sqrt{tψ}$ through the formula $$ \exp(-δ_t^2(x,y)) = \Ff[\frac{e^{-tψ}}{p_t(0)}](x-y) $$ where $\Ff$ denotes the Fourier transform. Thus we obtain the following "Gaussian" representation of the transition density: $p_t(x)=p_t(0) e^{-δ_t^2(x,0)}$ where $p_t(0)$ corresponds to a volume term related to $\sqrt{tψ}$ and where an "exponential" decay is governed by $δ_t^2$. This gives a complete and new geometric, intrinsic interpretation of $p_t(x)$.

math.PR↗