In [6], Serfozo introduced a class of stochastic processes which he called semi-stationary processes, and discussed elementary properties of these processes. Moreover, he presented ergodic theorems and functional central limit theorems with the uniformly strong mixing condition for them. These processes are a generalization of strictly stationary processes. Hereafter stationary means strictly stationary. The object of this paper is to prove the functional central limit theorems for the semi-stationary processes with the strong mixing condition. These results contain as special cases the corresponding theorems for the stationary processes (Theorem 1, Theorem 2 in [4])
Pre-print; version dated May 1999This paper gives new conditions for the functional central limit th...
AbstractWeak invariance principles for certain continuous time parameter stochastic processes (inclu...
We prove a self normalized central limit theorem for a new mixing class of processes introduced in K...
The object of this paper is to prove the functional central limit theorem for the stationary process...
A random functional central limit theorem is obtained for a stationary linear process of the form , ...
AbstractThe proofs of various central limit theorems for strictly stationary sequences of random var...
We establish a new class of functional central limit theorems for partial sum of certain symmetric ...
AbstractMany of the proofs of various central limit theorems and laws of the iterated logarithm for ...
In this note a functional central limit theorem for [varrho]-mixing sequences of I. A. Ibragimov (Th...
This paper shows how the modern machinery for generating abstract empirical central limit theorems c...
Many of the proofs of various central limit theorems and laws of the iterated logarithm for strictly...
This paper shows how the modern machinery for generating abstract empirical central limit theorems c...
We present almost sure central limit theorems for stochastic processes whose time parameter ranges o...
Weak invariance principles for certain continuous time parameter stochastic processes (including mar...
In this paper, we establish a functional central limit theorem, a law of the iterated logarithm and ...
Pre-print; version dated May 1999This paper gives new conditions for the functional central limit th...
AbstractWeak invariance principles for certain continuous time parameter stochastic processes (inclu...
We prove a self normalized central limit theorem for a new mixing class of processes introduced in K...
The object of this paper is to prove the functional central limit theorem for the stationary process...
A random functional central limit theorem is obtained for a stationary linear process of the form , ...
AbstractThe proofs of various central limit theorems for strictly stationary sequences of random var...
We establish a new class of functional central limit theorems for partial sum of certain symmetric ...
AbstractMany of the proofs of various central limit theorems and laws of the iterated logarithm for ...
In this note a functional central limit theorem for [varrho]-mixing sequences of I. A. Ibragimov (Th...
This paper shows how the modern machinery for generating abstract empirical central limit theorems c...
Many of the proofs of various central limit theorems and laws of the iterated logarithm for strictly...
This paper shows how the modern machinery for generating abstract empirical central limit theorems c...
We present almost sure central limit theorems for stochastic processes whose time parameter ranges o...
Weak invariance principles for certain continuous time parameter stochastic processes (including mar...
In this paper, we establish a functional central limit theorem, a law of the iterated logarithm and ...
Pre-print; version dated May 1999This paper gives new conditions for the functional central limit th...
AbstractWeak invariance principles for certain continuous time parameter stochastic processes (inclu...
We prove a self normalized central limit theorem for a new mixing class of processes introduced in K...