ЭБ Коллекция:

Asymptotic Behavior of the Summarized Square Error in Dependence Dose-Effect for Indirect Observations

Mon, 01 Jan 2007 00:00:00 GMT

Заглавие документа: Asymptotic Behavior of the Summarized Square Error in Dependence Dose-Effect for Indirect Observations Авторы: Tikhov, M. S.; Krishtopenko, D. S. Аннотация: The goal of this paper is to declare results of the asymptotic behavior of the summarized square error of the kernel distribution function estimator Fn(x) defined by SUm = m j =1(Fn(xj).F(xj))2, where F(x) is the unknown distribution function of a random variable X, ѓЦ(x) is the weight function in dose-response dependence on the sample U(n) = {(Wi, Yi), 1 . i . n}, Wi = I(Xi < Ui) is the indicator of even (Xi < Ui) and Y is a random variable, statistically dependant by U. We apply this result to test goodness-of-fit of the distribution function F(x).

Asymptotic Expansion in the Central Limit Theorem for an AR(1) Process

Mon, 01 Jan 2007 00:00:00 GMT

Заглавие документа: Asymptotic Expansion in the Central Limit Theorem for an AR(1) Process Авторы: Shmuratko, A. S. Аннотация: Consider an AR(1) process with i.i.d. innovations. We assume that the innovations have the finite fourth moment and density satisfying the integral Lipschitz condition. For such a process the asymptotic expansion of order 1 in the central limit theorem is obtained.

Random Integral Equations and Equations with Variational Derivatives Associated with Them

Mon, 01 Jan 2007 00:00:00 GMT

Заглавие документа: Random Integral Equations and Equations with Variational Derivatives Associated with Them Авторы: Romanovski, I. V.; Yanovich, L. A. Аннотация: We consider a nonlinear random integral equation and build the associated equation with variational derivatives in unknown characteristic functional of the triple (x, y, k), where x is the unknown function, y is the right-hand side of the initial equation, k is the kernel of the integral operator.

Investigation of Idle Time Model in Computer Networks

Mon, 01 Jan 2007 00:00:00 GMT

Заглавие документа: Investigation of Idle Time Model in Computer Networks Авторы: Minkevicius, S.; Kulvietis, G. Аннотация: An open queueing network model in light traffic has been developed. The probability limit theorem for the idle time process of customers in heavy traffic in open queueing networks has been presented. Finally, we present an application of the theorem - an idle time model from computer network practice.