DOI QR코드

DOI QR Code

ON THE WEAK LAW FOR WEIGHTED SUMS INDEXED BY RANDOM VARIABLES UNDER NEGATIVELY ASSOCIATED ARRAYS

  • Baek, Jong-Il (School of Mathematics & Informational Statistics and Institute of Basic Natural Science Wonkwang University) ;
  • Lee, Dong-Myong (School of Mathematics & Informational Statistics and Institute of Basic Natural Science Wonkwang University)
  • 발행 : 2003.01.01

초록

Let {$X_{nk}$\mid$1\;{\leq}\;k\;{\leq}\;n,\;n\;{\geq}\;1$} be an array of row negatively associated (NA) random variables which satisfy $P($\mid$X_{nk}$\mid$\;>\;x)\;{\leq}\;P($\mid$X$\mid$\;>\;x)$. For weighed sums ${{\Sigma}_{k=1}}^{Tn}\;a_kX_{nk}$ indexed by random variables {$T_n$\mid$n\;{\geq}$1$}, we establish a general weak law of large numbers (WLLN) of the form $({{\Sigma}_{k=1}}^{Tn}\;a_kX_{nk}\;-\;v_{[nk]})\;/b_{[an]}$ under some suitable conditions, where $\{a_n$\mid$n\;\geq\;1\},\; \{b_n$\mid$n\;\geq\;1\}$ are sequences of constants with $a_n\;>\;0,\;0\;<\;b_n\;\rightarrow \;\infty,\;n\;{\geq}\;1$, and {$v_{an}$\mid$n\;{\geq}\;1$} is an array of random variables, and the symbol [x] denotes the greatest integer in x.

키워드

참고문헌

  1. Stochastic Anal. Appl. v.5 Some general strong laws for weighted sums of stochastically dominated random variables A. Adler;A. Rosalsky https://doi.org/10.1080/07362998708809104
  2. Internat, J. math. Sci. v.14 On the weak law of large number for normed weighted sums of iid random variables A. Adler;A. Rosalsky https://doi.org/10.1155/S0161171291000182
  3. J. Multivariate Ana. v.37 A weak law for normed weight ed sums of random elements in Rademacher Type p Banach Space A. Adler;A. Rosalsky;R. L. Taylor https://doi.org/10.1016/0047-259X(91)90083-E
  4. Comm. Statist. v.A10 Positive dependence in multivariate distributions K. Alam;K. M. Lal Saxena
  5. Probability Theory: Independence, Interchange ability, Martingales(2nd ed.) Y. S. Chow;H. Teicher
  6. Amer. J. Math. v.68 A limiting theorem for random variables with infinite moments W. Feller https://doi.org/10.2307/2371837
  7. Statist. Probab. Lett. v.14 The weak law of large numbers for arrays A. Gut https://doi.org/10.1016/0167-7152(92)90209-N
  8. Ann. Statist. v.11 Negative association of random variables with applications K. Joag-Dev;F. Proschan https://doi.org/10.1214/aos/1176346079
  9. Theory and Application of infinite series(2nd english ed.) K. Knopp
  10. Ann. Univ. Mariae Curie-sklodovska Sect. A LI v.1 On the weak law of large numbers for randomly indexed partial sums for arrays P. Kowalski;Z. Rychlik
  11. Ann. Math. Statist. v.37 Some concept of dependence E. L. Lehmann https://doi.org/10.1214/aoms/1177699260
  12. Probability Theory I(4th ed.) M. Loeve
  13. Statist. Probab. Lett. v.15 A note on the almost sure convergence of sums of negatively dependent random variables P. Matula https://doi.org/10.1016/0167-7152(92)90191-7
  14. IMS Lecture Notes Monogr. Ser. 5. Ins Math. Statist. Asymptotic independence and limit theorems for positively and negatively dependent random variables, in Inequalities in Statistics and Probability C. M. Newman;Y. L. Tong(ed.)
  15. Ann. probab. v.9 A limit theorem for double arrays A. Rosalsky;H. Teicher https://doi.org/10.1214/aop/1176994418
  16. Ann. Probab. A comparison theorem on maximal inequalities between negatively associated and independent random variables Q. M. Shao
  17. Theory of Probab. & Its Appli. v.46 no.2 On the logarithm law for strictly stationary and negatively associated arrays C. Su;T. Hu;H. Liang https://doi.org/10.1137/S0040585X97979020