Strong Laws of Large Numbers for Random Walks Associated with a Class of One-Dimensional Convolution Structures.
The aim of the paper is to establish strong laws of large numbers for sequences of blockwise and pairwise -dependent random variables in a convex combination space with or without compactly uniformly integrable condition. Some of our results are even new in the case of real random variables.
In this paper we are concerned with the norm almost sure convergence of series of random vectors taking values in some linear metric spaces and strong laws of large numbers for sequences of such random vectors. Section 2 treats the Banach space case where the results depend upon the geometry of the unit cell. Section 3 deals with spaces equipped with a non-necessarily homogeneous -norm and in Section 4 we restrict our attention to sequences of identically distributed random vectors.
In this paper we get some results about the asymptotic behaviour of the sequenceΠn = 1 + X1 + X1X2 + X1X2X3 + ...where {Xn}n=1∞ are i.i.d. random variables. Strong limit laws, Central limit theorem and Iterated Logarithm law are obtained, after an analysis of the convergence of Πn. Rates of convergence are also given.
The problem of finding simple additional conditions, for a weakly convergent sequence in , which would suffice to imply strong convergence has been widely studied in recent years. In this Note we study this problem for Banach valued random vectors, by replacing weak convergence with a less restrictive assumption. Moreover, all the additional conditions we consider are also necessary for strong convergence, and they depend only on marginal distributions.
Let [0;a₁(x),a₂(x),…] be the regular continued fraction expansion of an irrational x ∈ [0,1]. We prove mainly that, for α > 0, β ≥ 0 and for almost all x ∈ [0,1], if α < 1 and β ≥ 0, if α = 1 and β < 1, and, if α > 1 or α = 1 and β >1, , , where if and otherwise, for all i ∈ 1,…,n.