MARCINKIEWICZ-TYPE LAW OF LARGE NUMBERS FOR DOUBLE ARRAYS

  • Hong, Dug-Hun (School of Mechanical and Automotive Engineering Catholic University of Taegu-Hyosung) ;
  • Volodin, Andrei I. (Research Institute of mathematics and mechanics Kazan State University)
  • Published : 1999.11.01

Abstract

Chaterji strengthened version of a theorem for martin-gales which is a generalization of a theorem of Marcinkiewicz proving that if $X_n$ is a sequence of independent, identically distributed random variables with $E{\mid}X_n{\mid}^p\;<\;{\infty}$, 0 < P < 2 and $EX_1\;=\;1{\leq}\;p\;<\;2$ then $n^{-1/p}{\sum^n}_{i=1}X_i\;\rightarrow\;0$ a,s, and in $L^p$. In this paper, we probe a version of law of large numbers for double arrays. If ${X_{ij}}$ is a double sequence of random variables with $E{\mid}X_{11}\mid^log^+\mid X_{11}\mid^p\;<\infty$, 0 < P <2, then $lim_{m{\vee}n{\rightarrow}\infty}\frac{{\sum^m}_{i=1}{\sum^n}_{j=1}(X_{ij-a_{ij}}}{(mn)^\frac{1}{p}}\;=0$ a.s. and in $L^p$, where $a_{ij}$ = 0 if 0 < p < 1, and $a_{ij}\;=\;E[X_{ij}\midF_[ij}]$ if $1{\leq}p{\leq}2$, which is a generalization of Etemadi's marcinkiewicz-type SLLN for double arrays. this also generalize earlier results of Smythe, and Gut for double arrays of i.i.d. r.v's.

Keywords

References

  1. Ann. of Math. Statist. v.40 An $L^P$-convergence theorem Chatterji, S. D.
  2. A course in probability theory(2nd ed.) Chung, K. L.
  3. Ann. Math. Statist v.36 Inequalities for the rth absolute moment of a sum of random variables,1≤r≤2 Esseen, C.;Von Bahr, B.
  4. Z. Wahrsch. Verw. Gebiete v.55 An elementary proof of the strong law of large numbers Etermadi, N.
  5. Ann. of Probab. v.3 Marcinkiewicz laws and convergence rate in the law of large numbers for random variables with multidimensional indices Gut, A.
  6. An introduction to the theory of numbers(4th ed.) Hardy, G. H.;Wright, E. M.
  7. Ann. of Probab. v.1 Strong laws of large numbers for r-dimensional arrays of random variables Smythe, R. T.
  8. Almost sure convergence Stout, W. F.