• Title/Summary/Keyword: Asymptotically almost negatively associated random variables

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A STRONG LAW OF LARGE NUMBERS FOR AANA RANDOM VARIABLES IN A HILBERT SPACE AND ITS APPLICATION

  • Ko, Mi-Hwa
    • Honam Mathematical Journal
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    • v.32 no.1
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    • pp.91-99
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    • 2010
  • In this paper we introduce the concept of asymptotically almost negatively associated random variables in a Hilbert space and obtain the strong law of large numbers for a strictly stationary asymptotically almost negatively associated sequence of H-valued random variables with zero means and finite second moments. As an application we prove a strong law of large numbers for a linear process generated by asymptotically almost negatively random variables in a Hilbert space with this result.

CONVERGENCE RATE IN STRONG LAW FOR ARRAYS OF ROWWISE AANA RANDOM VARIABLES

  • Han, Kwang-Hee
    • Journal of the Chungcheong Mathematical Society
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    • v.26 no.1
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    • pp.137-145
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    • 2013
  • In this paper we obtain the complete convergence of weighted sums of asymptotically almost negatively associated random variables. Some previous known results for negatively associated random variables are generalized to asymptotically almost negative association case.

Complete convergence for weighted sums of AANA random variables

  • Kim, Tae-Sung;Ko, Mi-Hwa
    • Proceedings of the Korean Statistical Society Conference
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    • 2002.11a
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    • pp.209-213
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    • 2002
  • We study maximal second moment inequality and derive complete convergence for weighted sums of asymptotically almost negatively associated(AANA) random variables by applying this inequality. 2000 Mathematics Subject Classification : 60F05

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COMPLETE CONVERGENCE FOR WEIGHTED SUMS OF AANA RANDOM VARIABLES AND ITS APPLICATION IN NONPARAMETRIC REGRESSION MODELS

  • Shen, Aiting;Zhang, Yajing
    • Journal of the Korean Mathematical Society
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    • v.58 no.2
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    • pp.327-349
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    • 2021
  • In this paper, we main study the strong law of large numbers and complete convergence for weighted sums of asymptotically almost negatively associated (AANA, in short) random variables, by using the Marcinkiewicz-Zygmund type moment inequality and Roenthal type moment inequality for AANA random variables. As an application, the complete consistency for the weighted linear estimator of nonparametric regression models based on AANA errors is obtained. Finally, some numerical simulations are carried out to verify the validity of our theoretical result.

MAXIMAL INEQUALITIES AND STRONG LAW OF LARGE NUMBERS FOR AANA SEQUENCES

  • Xuejun, Wang;Shuhe, Hu;Xiaoqin, Li;Wenzhi, Yang
    • Communications of the Korean Mathematical Society
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    • v.26 no.1
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    • pp.151-161
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    • 2011
  • Let {$X_n$, $n{\geq}1$} be a sequence of asymptotically almost negatively associated random variables and $S_n=\sum^n_{i=1}X_i$. In the paper, we get the precise results of H$\acute{a}$jek-R$\acute{e}$nyi type inequalities for the partial sums of asymptotically almost negatively associated sequence, which generalize and improve the results of Theorem 2.4-Theorem 2.6 in Ko et al. ([4]). In addition, the large deviation of $S_n$ for sequence of asymptotically almost negatively associated random variables is studied. At last, the Marcinkiewicz type strong law of large numbers is given.

On the Strong Laws for Weighted Sums of AANA Random Variables

  • Kim, Tae-Sung;Ko, Mi-Hwa;Chung, Sung-Mo
    • Journal of the Korean Statistical Society
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    • v.31 no.3
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    • pp.369-378
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    • 2002
  • Strong laws of large numbers for weighted sums of asymptotically almost negatively associated(AANA) sequence are proved by our generalized maximal inequality for AANA random variables at a crucial step.

ON THE COMPLETE CONVERGENCE FOR WEIGHTED SUMS OF DEPENDENT RANDOM VARIABLES UNDER CONDITION OF WEIGHTED INTEGRABILITY

  • Baek, Jong-Il;Ko, Mi-Hwa;Kim, Tae-Sung
    • Journal of the Korean Mathematical Society
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    • v.45 no.4
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    • pp.1101-1111
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    • 2008
  • Under the condition of h-integrability and appropriate conditions on the array of weights, we establish complete convergence and strong law of large numbers for weighted sums of an array of dependent random variables.