FUNCTIONAL CENTRAL LIMIT THEOREMS FOR SUMS OF NEARLY NONSTATIONARY PROCESSES

For a supercritical branching process (Z n ) in a stationary and ergodic envi- ronment ξ, we study the rate of convergence of the normalized population W n = Z n /E[Z n | ξ] to

We then derive rates in the central limit theorem for weighted sums of such randoms fields via an approximation by m-dependent random fields.. Introduction and

Kiessling and Lancellotti [KL06] have shown that, if the coefficients of this partial differential equation for the Ornstein-Uhlenbeck process are chosen to be constant functionals

exponential Young funtions for stationary real random elds whih are bounded.. or satisfy some nite exponential

We prove functional central and non-central limit theorems for generalized varia- tions of the anisotropic d-parameter fractional Brownian sheet (fBs) for any natural number d..

Central and non-central limit theorems for weighted power variations of fractional Brownian motion.. Ivan Nourdin a , David Nualart b,1 and

The central limit theorem (1.12) for the simple exclusion process was established by Ferrari and Fonte [5] in two cases, either when the η-process is in equilibrium, or when g(x) is

Key words: central limit theorem, invariance principle, strictly stationary process, maximal inequality, strong mixing, absolute regularity, Markov