1 Suppose we are given two probability measures on the set of one-way infinite finite-alphabet sequences. Consider the question when one of the measures predicts the other, that is, when conditional probabilities converge (in a certain sense), if one of the measures is chosen to generate the sequence. This question may be considered a refinement of the problem of sequence prediction in its most...

We consider some classes of stationary, counting{measure{valued Markov processes and their companions under time{reversal. Examples arise in the L evy{It^ o decomposition of stable Ornstein{Uhlenbeck processes, the large{time asymptotics of the standard additive coalescent, and extreme value theory. These processes share the common feature that points in the support of the evolving counting{ me...

simple harmonizable processes (shp) introduced by soltani and parvardeh (2006) are a large class of nonstationary processes which includes stationary and periodically correlated (pc) processes. detection and estimation of shp structure are important problems when dealing with nonstationary data. in this paper, we study the spectral properties of simple processes and propose a method to detect a...

We consider a continuous-time stochastic volatility model. The model contains a stationary volatility process, the multivariate density of the finite dimensional distributions of which we aim to estimate. We assume that we observe the process at discrete instants in time. The sampling times will be equidistant with vanishing distance. A multivariate Fourier-type deconvolution kernel density est...

The notion of stability can be generalised to point processes by defining the scaling operation in a randomised way: scaling a configuration by t corresponds to letting such a configuration evolve according to a Markov branching particle system for -log t time. We prove that these are the only stochastic operations satisfying basic associativity and distributivity properties and we thus introdu...