Large deviations for generic stationary processes
Let (Ω,A,μ,T) be a measure preserving dynamical system. The speed of convergence in probability in the ergodic theorem for a generic function on Ω is arbitrarily slow.
Level crossings and other level functionals of stationary Gaussian processes.
Limit theorems for Banach-valued autoregressive processes. Applications to real continuous time processes.
Limit theory for some positive stationary processes with infinite mean
We prove stable limit theorems and one-sided laws of the iterated logarithm for a class of positive, mixing, stationary, stochastic processes which contains those obtained from nonintegrable observables over certain piecewise expanding maps. This is done by extending Darling–Kac theory to a suitable family of infinite measure preserving transformations.
Linear approximations to some non-linear AR(1) processes
Some methods for approximating non-linear AR(1) processes by classical linear AR(1) models are proposed. The quality of approximation is studied in special non-linear AR(1) models by means of comparisons of quality of extrapolation and interpolation in the original models and in their approximations. It is assumed that the white noise has either rectangular or exponential distribution.
Linear predictor for stationary processes in complete correlated actions
Linear rescaling of the stochastic process
Discussion on the limits in distribution of processes under joint rescaling of space and time is presented in this paper. The results due to Lamperti (1962), Weissman (1975), Hudson Mason (1982) and Laha Rohatgi (1982) are improved here.
Linear transformations of locally stationary processes
The paper deals with linear transformations of harmonizable locally stationary random processes. Necessary and sufficient conditions under which a linear transformation defines again a locally stationary process are given.
Loi de probabilité des maxima d'une fonction aléatoire stationnaire Somme d'une partie gaussienne et d'une partie sinusoïdale
Long memory time series models
Long time behaviour and stationary regime of memory gradient diffusions
In this paper, we are interested in a diffusion process based on a gradient descent. The process is non Markov and has a memory term which is built as a weighted average of the drift term all along the past of the trajectory. For this type of diffusion, we study the long time behaviour of the process in terms of the memory. We exhibit some conditions for the long-time stability of the dynamical system and then provide, when stable, some convergence properties of the occupation measures and of the...
Long-memory stable Ornstein-Uhlenbeck processes.
Maxima and minima of stationary random sequences under a local dependence restriction.
Mixing conditions for multivariate infinitely divisible processes with an application to mixed moving averages and the supOU stochastic volatility model
We consider strictly stationary infinitely divisible processes and first extend the mixing conditions given in Maruyama [Theory Probab. Appl. 15 (1970) 1–22] and Rosiński and Żak [Stoc. Proc. Appl. 61 (1996) 277–288] from the univariate to the d-dimensional case. Thereafter, we show that multivariate Lévy-driven mixed moving average processes satisfy these conditions and hence a wide range of well-known processes such as superpositions of Ornstein − Uhlenbeck (supOU) processes or (fractionally integrated)...
Models of Alternating Renewal Process at Discrete Time
We study a class of models used with success in the modelling of climatological sequences. These models are based on the notion of renewal. At first, we examine the probabilistic aspects of these models to afterwards study the estimation of their parameters and their asymptotical properties, in particular the consistence and the normality. We will discuss for applications, two particular classes of alternating renewal processes at discrete time. The first class is defined by laws of sojourn time...
Moderate deviations for stationary sequences of bounded random variables
In this paper we derive the moderate deviation principle for stationary sequences of bounded random variables under martingale-type conditions. Applications to functions of ϕ-mixing sequences, contracting Markov chains, expanding maps of the interval, and symmetric random walks on the circle are given.
Moderate deviations of empirical periodogram and non-linear functionals of moving average processes
Moments of passage times for Lévy processes
Moments of some random functionals
The paper deals with nonnegative stochastic processes X(t,ω)(t ≤ 0) not identically zero with stationary and independent increments right-continuous sample functions and fulfilling the initial condition X(0,ω)=0. The main aim is to study the moments of the random functionals for a wide class of functions f. In particular a characterization of deterministic processes in terms of the exponential moments of these functionals is established.
Moving Shift Averages for Ergodic Transformations.