arXiv subjects

Jan Rosinski

Publications and source records attributed to Jan Rosinski.

8 recordsLinked to original sources

arXiv2017

Representations and isomorphism identities for infinitely divisible processes

We propose isomorphism type identities for nonlinear functionals of general infinitely divisible processes. Such identities can be viewed as an analogy of the Cameron-Martin formula for Poissonian infinitely divisible processes but with random translations. The applicability of these tools relies on a precise understanding of Lévy measures of infinitely divisible processes and their representations, which are developed here in full generality. We illustrate this approach on examples of squared Bessel processes, Feller diffusions, permanental processes, as well as Lévy processes.

math.PR↗

arXiv2014

Structure of infinitely divisible semimartingales

This paper gives a complete characterization of infinitely divisible semimartingales, i.e., semimartingales whose finite dimensional distributions are infinitely divisible. An explicit and essentially unique decomposition of such semimartingales is obtained. A new approach, combining series decompositions of infinitely divisible processes with detailed analysis of their jumps, is presented. As an ilustration of the main result, the semimartingale property is explicitely determined for a large class of stationary increment processes and several examples of processes of interest are considered. These results extend Stricker's theorem characterizing Gaussian semimartingales and Knight's theorem describing Gaussian moving average semimartingales, in particular.

math.PR↗

arXiv2014

General inverse problems for regular variation

Regular variation of distributional tails is known to be preserved by various linear transformations of some random structures. An inverse problem for regular variation aims at understanding whether the regular variation of a transformed random object is caused by regular variation of components of the original random structure. In this paper we build up on previous work and derive results in the multivariate case and in situations where regular variation is not restricted to one particular direction or quadrant.

math.PR↗

arXiv2013

Stochastic integral and series representations for strictly stable distributions

In this paper we find and develop a stochastic integral representation for the class of strictly stable distributions. We establish an explicit relationship between stochastic integral and shot-noise series representations of strictly stable distributions, which shows that the class of distributions representable by stochastic integral is larger than the class representable by a shot-noise series. This inclusion is proper when the stability index is greater than 1. We also give an explicit description of distributions possessing both representations.

math.PR↗

arXiv2012

On the mixing structure of stationary increment and self-similar symmetric α-stable processes

Mixed moving average processes appear in the ergodic decomposition of stationary symmetric α-stable (SαS) processes. They correspond to the dissipative part of "deterministic" flows generating SαS processes (Rosinski, 1995). Along these lines we study stationary increment and self-similar SαS processes. Since the classes of stationary increment and self-similar processes can be embedded into the class of stationary processes by the Masani and Lamperti transformations, respectively, we characterize these classes of SαS processes in terms of nonsingular flows and the related cocycles. We illustrate this approach considering various examples of self-similar mixed moving average SαS processes introduced in (Surgailis, Rosinski, Mandrekar and Cambanis, 1992).

math.PR↗

arXiv2011

Spatial Brownian motion in renormalized Poisson potential: A critical case

Let $B_s$ be a three dimensional Brownian motion and $ω(dx)$ be an independent Poisson field on $\mathbb{R}^3$. It is proved that for any $t>0$, conditionally on $ω(\cdot)$, \label{*} \mathbb{E}_0 \exp\{θ\int_0^t \bar{V}(B_s) ds\} \ < \infty \ a.s. & \text{if} θ< 1/16, \medskip = \infty \ a.s. & \text{if} θ> 1/16, where $\bar{V}(x)$ is the renormalized Poisson potential $$ \bar{V}(x)=\int_{\mathbb{R}^3} \frac{1}{| x-y |^2} \big[ω(dy)-dy\big]. $$ Then the long term behavior of the quenched exponential moment \eqref{*} is determined for $θ\in (0, 1/16)$ in the form of integral tests. This paper exhibits and builds upon the interrelation between the exponential moment \eqref{*} and the celebrated Hardy's inequality $$ \int_{\mathbb{R}^3} \frac{f^2(x)}{| x |^2} dx \le 4 \|\nabla f\|_2^2, 2in f \in W^{1,2}(\mathbb{R}^3). $$

math.PR↗

arXiv2010

Large deviations for local times and intersection local times of fractional Brownian motions and Riemann-Liouville processes

In this paper we prove exact forms of large deviations for local times and intersection local times of fractional Brownian motions and Riemann-Liouville processes. We also show that a fractional Brownian motion and the related Riemann-Liouville process behave like constant multiples of each other with regard to large deviations for their local and intersection local times. As a consequence of our large deviation estimates, we derive laws of iterated logarithm for the corresponding local times. The key points of our methods: (1) logarithmic superadditivity of a normalized sequence of moments of exponentially randomized local time of a fractional Brownian motion; (2) logarithmic subadditivity of a normalized sequence of moments of exponentially randomized intersection local time of Riemann-Liouville processes; (3) comparison of local and intersection local times based on embedding of a part of a fractional Brownian motion into the reproducing kernel Hilbert space of the Riemann-Liouville process.

math.PR↗

arXiv2009

Modeling and simulation with operator scaling

Self-similar processes are useful in modeling diverse phenomena that exhibit scaling properties. Operator scaling allows a different scale factor in each coordinate. This paper develops practical methods for modeling and simulating stochastic processes with operator scaling. A simulation method for operator stable Levy processes is developed, based on a series representation, along with a Gaussian approximation of the small jumps. Several examples are given to illustrate practical applications. A classification of operator stable Levy processes in two dimensions is provided according to their exponents and symmetry groups. We conclude with some remarks and extensions to general operator self-similar processes.

math.PR↗