This paper proposes an adaptive version for the Metropolis adjusted Langevin algorithm with a truncated drift (T-MALA). The scale parameter and the covariance matrix of the proposal kernel of the algorithm are simultaneously and recursively updated in order to reach the optimal acceptance rate...

We study a long-range dependence Gaussian process which we call “sub-fractional Brownian motion” (sub-fBm), because it is intermediate between Brownian motion (Bm) and fractional Brownian motion (fBm) in the sense that it has properties analogous to those of fBm, but the increments on...

In this paper we generalize Yu’s strong invariance principle for associated sequences to the multi-parameter case, under the assumption that the covariance coefficient u(n) decays exponentially as n - (infinity symbol). The main tools will be the Berkes-Morrow multi-parameter blocking...

We establish a mathematical framework that formally validates the two-phase “superpopulation viewpoint” proposed by Hartley and Sielken (1975), by defining a product probability space which includes both the design space and the model space. We develop a general methodology that combines...

In this paper, we use the Markov chain censoring technique to study infinite state Markov chains whose transition matrices possess block-repeating entries. We demonstrate that a number of important probabilistic measures are invariant under censoring. Informally speaking, these measures involve...

In the context of simulating the transport of a chemical or bacterial contaminant through a moving sheet of water, we extend a well established method of approximating reaction-diffusion equations with Markov chains by allowing convection, certain Poisson measure driving sources and a larger...

Several long-range dependence, self-similar Gaussian processes arise from asymptotics of some classes of spatially distributed particle systems and superprocesses. The simplest examples are fractional Brownian motion and sub-fractional fractional Brownian motion, the latter being intermediate...

We examine various conditions under which a weighted weak law of large numbers holds, in the context of noncommutative probability theory.

In this paper, we investigate several sample path properties on the increments of (N,d)-Gaussian random fields and also we obtain the law of iterated logarithm for the Gaussian random field, via estimating upper and lower bounds of large deviation probabilities on suprema of the (N,d)- Gaussian...

Herein, we characterize strong solutions of multidimensional stochastic differential equations (formula) that can be represented locally as (formula) where W is an multidimensional Brownian motion and U, (symbole) are continuous functions. Assuming that (symbole) is continuously differentiable,...