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Article Citation - WoS: 2Citation - Scopus: 3Uncorrelatedness and Correlatedness of Powers of Random Variables(Birkhauser verlag Ag, 2002) Ostrovska, SLet xi(1),...,xi(n) be random variables and U be a subset of the Cartesian prodnet Z(+)(n), Z(+) being the set of all non-negative integers. The random variables are said to be strictly U-uncorrelated if E(xi(1)(j1) ... xi(n)(jn)) = E(xi(1)(j1)) ... E(xi(n)(jn)) double left right arrow (j(1), ..., j(n)) is an element of U. It is proved that for an arbitrary subset U subset of or equal to Z(+)(n) containing all points with 0 or I non-zero coordinates there exists a collection of n strictly U-uncorrelated random variables.Article Citation - WoS: 36Citation - Scopus: 40On the Improvement of Analytic Properties Under the Limit Q-Bernstein Operator(Academic Press inc Elsevier Science, 2006) Ostrovska, SLet B-n(f, q; x), n = 1, 2,... be the q-Bernstein polynomials of a function f is an element of C[0, 1]. In the case 0 < q < 1, a sequence {B-n(f, q; x)} generates a positive linear operator B-infinity = B-infinity,B-q on C[0, 1], which is called the limit q-Bernstein operator In this paper, a connection between the smoothness of a function f and the analytic properties of its image under Boo is studied. (c) 2005 Elsevier Inc. All rights reserved.Article Citation - WoS: 17Citation - Scopus: 16The Approximation by q-bernstein Polynomials in the Case q ↓ 1(Springer Basel Ag, 2006) Ostrovska, SLet B-n (f, q; x), n = 1, 2, ... , 0 < q < infinity, be the q-Bernstein polynomials of a function f, B-n (f, 1; x) being the classical Bernstein polynomials. It is proved that, in general, {B-n (f, q(n); x)} with q(n) down arrow 1 is not an approximating sequence for f is an element of C[0, 1], in contrast to the standard case q(n) up arrow 1. At the same time, there exists a sequence 0 < delta(n) down arrow 0 such that the condition 1 <= q(n) <= delta(n) implies the approximation of f by {B-n(f, qn; x)} for all f is an element of C[0, 1].Article Citation - WoS: 4Citation - Scopus: 4Uncorrelatedness sets for random variables with given distributions(Amer Mathematical Soc, 2005) Ostrovska, SLet xi(1) and xi(2) be random variables having finite moments of all orders. The set U(xi(1),xi(2)) := {( j, l) is an element of N-2 : E(xi(1)(j)xi(2)(l)) = E(xi(1)(j)) E(xi(2)(l))} is said to be an uncorrelatedness set of xi(1) and xi(2). It is known that in general, an uncorrelatedness set can be arbitrary. Simple examples show that this is not true for random variables with given distributions. In this paper we present a wide class of probability distributions such that there exist random variables with given distributions from the class having a prescribed uncorrelatedness set. Besides, we discuss the sharpness of the obtained result.
