Invariance principle in a bilinear model with weak nonlinearity.
Invariance principle, multifractional gaussian processes and long-range dependence
This paper is devoted to establish an invariance principle where the limit process is a multifractional gaussian process with a multifractional function which takes its values in (1/2, 1). Some properties, such as regularity and local self-similarity of this process are studied. Moreover the limit process is compared to the multifractional brownian motion.
Invariance principles for absolutely regular empirical processes
Invariance principles for Brownian intersection local time and polymer measures.
Invariance Principles for Martingales and Sums of Indpendent Random Variables.
Invariance principles for random walks conditioned to stay positive
Let {Snbe a random walk in the domain of attraction of a stable law , i.e. there exists a sequence of positive real numbers ( an) such that Sn/anconverges in law to . Our main result is that the rescaled process (S⌊nt⌋/an, t≥0), when conditioned to stay positive, converges in law (in the functional sense) towards the corresponding stable Lévy process conditioned to stay positive. Under some additional assumptions, we also prove a related invariance principle for the random walk killed at its first...
Invariance principles for ranked excursion lengths and heights.
Invariance principles for spatial multitype Galton–Watson trees
We prove that critical multitype Galton–Watson trees converge after rescaling to the brownian continuum random tree, under the hypothesis that the offspring distribution is irreducible and has finite covariance matrices. Our study relies on an ancestral decomposition for marked multitype trees, and an induction on the number of types. We then couple the genealogical structure with a spatial motion, whose step distribution may depend on the structure of the tree in a local way, and show that the...
Invariance principles in Hölder spaces.
Invariance principles in
Large deviations for sample paths of Gaussian processes quadratic variations.
Law of the Iterated Logarithm for Tranisitive C... Anosov Flows and Semiflows over Maps of the Interval.
Laws of large numbers for -statistics.
Le drap brownien comme limite en loi des temps locaux linéaires
Les «principes d'invariance» en probabilité sur l'espace de Wiener
Limit laws for transient random walks in random environment on
We consider transient random walks in random environment on with zero asymptotic speed. A classical result of Kesten, Kozlov and Spitzer says that the hitting time of the level converges in law, after a proper normalization, towards a positive stable law, but they do not obtain a description of its parameter. A different proof of this result is presented, that leads to a complete characterization of this stable law. The case of Dirichlet environment turns out to be remarkably explicit.
Limit theorems for measure-valued processes of the level-exceedance type
Let, for each t∈T, ψ(t, ۔) be a random measure on the Borel σ-algebra in ℝd such that Eψ(t, ℝd)k < ∞ for all k and let (t, ۔) be its characteristic function. We call the function (t1,…, tl ; z1,…, zl) = of arguments l∈ ℕ, t1, t2… ∈T, z1, z2∈ ℝd the covaristic of the measure-valued random function (MVRF) ψ(۔, ۔). A general limit theorem for MVRF's in terms of covaristics is proved and applied to functions of the kind ψn(t, B) = µ{x : ξn(t, x) ∈B}, where μ is a nonrandom finite measure...
Limit theorems for measure-valued processes of the level-exceedance type
Let, for each t ∈ T, ψ(t, ۔) be a random measure on the Borel σ-algebra in ℝd such that Eψ(t, ℝd)k < ∞ for all kand let (t, ۔) be its characteristic function. We call the function (t1,…, tl ; z1,…, zl) = of argumentsl ∈ ℕ, t1, t2… ∈ T, z1, z2 ∈ ℝd the covaristic of the measure-valued random function (MVRF) ψ(۔, ۔). A general limit theorem for MVRF's in terms of covaristics is proved and applied to functions of the kind ψn(t, B) = µ{x : ξn(t, x) ∈ B}, where μ is a nonrandom finite measure...
Limit theorems for some functionals with heavy tails of a discrete time Markov chain
Consider an irreducible, aperiodic and positive recurrent discrete time Markov chain (Xn,n ≥ 0) with invariant distribution μ. We shall investigate the long time behaviour of some functionals of the chain, in particular the additive functional S n = ∑ i = 1 n f ( X i ) for a possibly non square integrable functionf. To this end we shall link ergodic properties of the chain to mixing properties, extending known results in the continuous time case. We will then use existing results of convergence...
Limiting behavior of the perturbed empirical distribution functions evaluated at -statistics for strongly mixing sequences of random variables.