• Title/Summary/Keyword: strong law

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EXTENSIONS OF SEVERAL CLASSICAL RESULTS FOR INDEPENDENT AND IDENTICALLY DISTRIBUTED RANDOM VARIABLES TO CONDITIONAL CASES

  • Yuan, De-Mei;Li, Shun-Jing
    • Journal of the Korean Mathematical Society
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    • v.52 no.2
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    • pp.431-445
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    • 2015
  • Extensions of the Kolmogorov convergence criterion and the Marcinkiewicz-Zygmund inequalities from independent random variables to conditional independent ones are derived. As their applications, a conditional version of the Marcinkiewicz-Zygmund strong law of large numbers and a result on convergence in $L^p$ for conditionally independent and conditionally identically distributed random variables are established, respectively.

SLIN FOR WEIGHTED SUMS OF STOCHASTICALLY DOMINATED PAIRWISE INDEPENDENT RANDOM VARIABLES

  • Sung, Soo-Hak
    • Communications of the Korean Mathematical Society
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    • v.13 no.2
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    • pp.377-384
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    • 1998
  • Let ${X_n,n \geq 1}$ be a sequence of stochatically dominated pairwise independent random variables. Let ${a_n, n \geq 1}$ and ${b_n, n \geq 1}$ be seqence of constants such that $a_n \neq 0$ and $0 < b_n \uparrow \infty$. A strong law large numbers of the form $\sum^{n}_{j=1}{a_j X_i//b_n \to 0$ almost surely is obtained.

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ON THE EXPONENTIAL INEQUALITY FOR NEGATIVE DEPENDENT SEQUENCE

  • Kim, Tae-Sung;Kim, Hyun-Chull
    • Communications of the Korean Mathematical Society
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    • v.22 no.2
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    • pp.315-321
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    • 2007
  • We show an exponential inequality for negatively associated and strictly stationary random variables replacing an uniform boundedness assumption by the existence of Laplace transforms. To obtain this result we use a truncation technique together with a block decomposition of the sums. We also identify a convergence rate for the strong law of large number.

On the Strong Law of Large Numbers for Convex Tight Fuzzy Random Variables

  • Joo Sang Yeol;Lee Seung Soo
    • Proceedings of the Korean Statistical Society Conference
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    • 2001.11a
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    • pp.137-141
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    • 2001
  • We can obtain SLLN's for fuzzy random variables with respect to the new metric $d_s$ on the space F(R) of fuzzy numbers in R. In this paper, we obtain a SLLN for convex tight random elements taking values in F(R).

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On the strong law of large numbers for pairwise negative quadrant dependent random variables

  • T. S.;J. I.;H. Y.
    • Communications for Statistical Applications and Methods
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    • v.7 no.1
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    • pp.291-296
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    • 2000
  • Petrov(1996) examined the connection between general moment conditions and the applicability of the strong law lf large numbers to a sequence of pairwise independnt and identically distributed random variables. In this note wee generalize Theorem 1 of Petrov(1996) and also show that still holds under assumption of pairwise negative quadrant dependence(NQD).

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POWER INEQUALITY ON THE SIMPLEX

  • Baek, In-Soo
    • Journal of the Chungcheong Mathematical Society
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    • v.25 no.2
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    • pp.313-318
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    • 2012
  • The power inequality ${\prod}_{k=1}^{N}\;{x}_{k}^{x_{k}}\;{\geq}\;{\prod}_{k=1}^{N}\;{p}_{k}^{x_{k}}$ holds for the points $(x_1,{\ldots},x_N),(p_1,{\ldots},p_N)$ of the simplex. We show this using the analytic method combining Frostman's density theorem with the strong law of large numbers.

ON THE ALMOST SURE CONVERGENCE OF WEIGHTED SUMS OF NA RANDOM VARIABLES

  • Kim, T.S.;Ko, M.H.;Lee, Y.M.;Lin, Z.
    • Journal of the Korean Statistical Society
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    • v.33 no.1
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    • pp.99-106
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    • 2004
  • Let {X, $X_{n}, n\;{\geq}\;1$} be a sequence of identically distributed, negatively associated (NA) random variables and assume that $│X│^{r}$, r > 0, has a finite moment generating function. A strong law of large numbers is established for weighted sums of these variables.

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.

The Strong Laws of Large Numbers for Weighted Averages of Dependent Random Variables

  • Kim, Tae-Sung;Lee, Il-Hyun;Ko, Mi-Hwa
    • Communications for Statistical Applications and Methods
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    • v.9 no.2
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    • pp.451-457
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    • 2002
  • We derive the strong laws of large numbers for weighted averages of partial sums of random variables which are either associated or negatively associated. Our theorems extend and generalize strong law of large numbers for weighted sums of associated and negatively associated random variables of Matula(1996; Probab. Math. Statist. 16) and some results in Birkel(1989; Statist. Probab. Lett. 7) and Matula (1992; Statist. Probab. Lett. 15 ).