A resummed branching process representation for a class of nonlinear ODEs.
A reversibility problem for Fleming-Viot processes.
A review of discrete-time risk models.
A Riemann approach to random variation
This essay outlines a generalized Riemann approach to the analysis of random variation and illustrates it by a construction of Brownian motion in a new and simple manner.
A robust spectral method for finding lumpings and meta stable states of non-reversible Markov chains.
A scalarization technique for computing the power and exponential moments of Gaussian random matrices.
A scaling result for explosive processes.
A second order approximation for the inverse of the distribution function of the sample mean
The classical quantile approximation for the sample mean, based on the central limit theorem, has been proved to fail when the sample size is small and we approach the tail of the distribution. In this paper we will develop a second order approximation formula for the quantile which improves the classical one under heavy tails underlying distributions, and performs very accurately in the upper tail of the distribution even for relatively small samples.
A second order SDE for the Langevin process reflected at a completely inelastic boundary
It was shown in [2] that a Langevin process can be reflected at an energy absorbing boundary. Here, we establish that the law of this reflecting process can be characterized as the unique weak solution to a certain second order stochastic differential equation with constraints, which is in sharp contrast with a deterministic analog.
A second-order stochastic dominance portfolio efficiency measure
In this paper, we introduce a new linear programming second-order stochastic dominance (SSD) portfolio efficiency test for portfolios with scenario approach for distribution of outcomes and a new SSD portfolio inefficiency measure. The test utilizes the relationship between CVaR and dual second-order stochastic dominance, and contrary to tests in Post [Post] and Kuosmanen [Kuosmanen], our test detects a dominating portfolio which is SSD efficient. We derive also a necessary condition for SSD efficiency...
A semigroup charaterization of the multiparameter Wiener process.
A semigroup setting for distance measures in connexion with Poisson approximation.
A semigroup-theoretic proof of Poisson's limit law.
A semigroup-theoretic proof of the law of large numbers.
A semi-markovian model for the brownian motion
A semimartingale characterization of average optimal stationary policies for Markov decision processes.
A sharp analysis on the asymptotic behavior of the Durbin–Watson statistic for the first-order autoregressive process
The purpose of this paper is to provide a sharp analysis on the asymptotic behavior of the Durbin–Watson statistic. We focus our attention on the first-order autoregressive process where the driven noise is also given by a first-order autoregressive process. We establish the almost sure convergence and the asymptotic normality for both the least squares estimator of the unknown parameter of the autoregressive process as well as for the serial correlation estimator associated with the driven noise....
A sharp maximal inequality for continuous martingales and their differential subordinates
Assume that , are continuous-path martingales taking values in , , such that is differentially subordinate to . The paper contains the proof of the maximal inequality The constant is shown to be the best possible, even in the one-dimensional setting of stochastic integrals with respect to a standard Brownian motion. The proof uses Burkholder’s method and rests on the construction of an appropriate special function.
A Sharper Form of the Doeblin-Lévy-Kolmogorov-Rogozin Inequality for Concentration Functions.
A short proof of decomposition of strongly reduced martingales