A maximal inequality for partial sums of finite exchangeable sequences of random variables

Let be a finite exchangeable sequence of Banach space valued random variables, i.e., a sequence such that all joint distributions are invariant under permutations of the variables. We prove that there is an absolute constant such that if , then

for all . This generalizes an inequality of Montgomery-Smith and Lata{\l}a for independent and identically distributed random variables. Our maximal inequality is apparently new even if is an infinite exchangeable sequence of random variables. As a corollary of our result, we obtain a comparison inequality for tail probabilities of sums of arbitrary random variables over random subsets of the indices.

     

The distribution of partially exchangeable random variables

In this article, we derive the distribution of partially exchangeable binary random variables, generalizing the distribution of exchangeable binary random variables and hence the binomial distribution. The distribution can be viewed as a mixture of Markov chains. We introduce rectangular complete monotonicity and show that partial exchangebility can be characterized by rectangular complete monotonicity. The distribution aided with rectangular complete monotonicity can be used to analyze serially correlated data common in many areas of science.     

Order statistics from mixed exchangeable random variables

Two different exchangeable samples are considered and these two samples are assumed to be independent of each other. From these two samples a new sample is combined and treated as a single set of observations. The distribution of a single order statistic and the joint distribution of two order statistics for a new mixed sample are derived and expressed in terms of joint distribution functions. As a special case the distribution of a single order statistic and the joint distribution of two nonadjacent order statistics from exchangeable random variables are obtained. The results presented in this paper allows widespread applications in modelling of various lifetime data, biomedical sciences, reliability and survival analysis, actuarial sciences etc., where the assumption of independence of data cannot be accepted and the exchangeability is a more realistic assumption.     

Almost sure Cesàro and Euler summability of sequences of dependent random variables

For a sequence of real random variables C _α-summability is shown under conditions on the variances of weighted sums, comprehending and sharpening strong laws of large numbers (SLLN) of Rademacher-Menchoff and Cramér-Leadbetter, respectively. Further an analogue of Kolmogorov’s criterion for the SLNN is established for E _α-summability under moment and multiplicativity conditions of 4th order, which allows one to weaken Chow’s independence assumption for identically distributed square integrable random variables. The simple tool is a composition of Cesàro-type and of Euler summability methods, respectively. Received: 12 June 2006, Revised: 14 May 2007     

Representations for partially exchangeable arrays of random variables

Consider an array of random variables (X_i,j), 1 ≤ i,j < ∞, such that permutations of rows or of columns do not alter the distribution of the array. We show that such an array may be represented as functions f(α, ξ_i, η_j, λ_i,j) of underlying i.i.d, random variables. This result may be useful in characterizing arrays with additional structure. For example, we characterize random matrices whose distribution is invariant under orthogonal rotation, confirming a conjecture of Dawid.     

Almost periodic random sequences in probability

In this paper almost periodic random sequence in probability is defined and investigated. It is also applied to random difference equations by means of exponential dichotomy. The existence of such kind of solutions of random difference equations is discussed.     

Almost sure limit theorems for random sums of multiindex random variables

In this paper, we obtain an almost sure functional limit theorem for random sums of multiindex random variables.     

Some partial orderings of exchangeable random variables by positive dependence

Some partial orderings of positively dependent exchangeable random variables are introduced. The interrelations among them, the inequalities which follow from them and two models which yield such partial orderings are then discussed. Particular examples include ordering multivariate normal, t, χ², Cauchy, exponential, binomial, Poisson, gamma and Farlie-Gumbel-Morgenstern random vectors. Applications to genetic selection and choice of sampling procedures are given.     

Structure of exchangeable infinitely divisible sequences of poisson random vectors

De Finetti's Theorem reveals a simple explicit structure for an infinite exchangeable sequence of zero-one random variables. Although more general results are known, simple explicit results might be expected in particular settings. In this paper such results are obtained for exchangeable sequences of infinitely divisible Poisson random variables and random vectors. The methods employed are elementary, except in that they involve appeal to moment theorems.     

Minima of sequences of Gaussian random variables

For a given sequence of real numbers $a_1,\dots ,a_n$ we denote the k-th smallest one by $k\text{-}{\min }_{1?i?n}{a}_i$. We show that there exist two absolute positive constants c and C such that for every sequence of positive real numbers $x_1,\dots ,x_n$ and every $k?n$ one has

$c\underset{1?j?k}{\max }\frac{k+1?j}{{\sum }_{i=j}^{n}1/x_i}?\mathbb{E}k\text{-}\underset{1?i?n}{\min }|x_i{g}_i|?C\ln (k+1)\underset{1?j?k}{\max }\frac{k+1?j}{{\sum }_{i=j}^{n}1/x_i},$

where $g_i\in N(0,1)$, $i=1,\dots ,n$, are independent Gaussian random variables. Moreover, if $k=1$ then the left hand side estimate does not require independence of the $g_i$s. Similar estimates hold for $\mathbb{E}k\text{-}{\min }_{1?i?n}{|x_i{g}_i|}^p$ as well. To cite this article: Y. Gordon et al., C. R. Acad. Sci. Paris, Ser. I 340 (2005).     

Almost sure versions of limit theorems for random sums of multiindex random variables

In this paper we obtain an almost sure version of a limit theorem for random sums of multiindex random variables that belong to the domain of attraction of a p-stable law.     

Convergence of sequences of pairwise independent random variables

In spite of the fact that the tail -algebra of a sequence of pairwise independent random variables may not be trivial, we have discovered that if such a sequence converges in probability or almost everywhere, then the limit has to be a constant. This enables us to provide necessary and sufficient conditions for its convergence, in terms of its marginal distribution functions.

     

On the uniform distribution of sequences of random variables

Summary This paper deals with the almost sure uniform distribution (modulo 1) of sequences of random variables. In the case where the law of the increments X _n+h –X _n of the sequence X ₀, X ₁, does not depend on n, sufficient conditions are given to assure the uniform distribution (modulo 1) with probability one. As an illustrative example the partial sums of a sequence of independent, identically distributed variables is considered.     

Comparison of moments for tangent sequences of random variables

Summary It is shown that for all tangent sequences (d _n) and (e _n) of nonnegative or conditionally symmetric random variables and for every function satisfying the growth condition (2x)(x) the following inequality holds: . This generalizes results of J. Zinn and proves a conjecture of S. Kwapie and W.A. Woyczyski.