• 제목/요약/키워드: linearly negative quadrant random variables

검색결과 7건 처리시간 0.017초

선형 음의 사분 종속확률변수에서 가중합에 대한 수렴성 연구 (Convergence of weighted sums of linearly negative quadrant dependent random variables)

  • 이승우;백종일
    • 한국신뢰성학회지:신뢰성응용연구
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    • 제12권4호
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    • pp.265-274
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    • 2012
  • We in this paper discuss the strong law of large numbers for weighted sums of arrays of rowwise LNQD random variables by using a new exponential inequality of LNQD r.v.'s under suitable conditions and we obtain one of corollary.

On Convergence of Weighted Sums of LNQD Random

  • Kim, So-Youn;Baek, Jong-Il
    • Communications for Statistical Applications and Methods
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    • 제19권5호
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    • pp.647-654
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    • 2012
  • We discuss the strong convergence for weighted sums of linearly negative quadrant dependent(LNQD) random variables under suitable conditions and the central limit theorem for weighted sums of an LNQD case is also considered. In addition, we derive some corollaries in LNQD setting.

A CENTRAL LIMIT THEOREM FOR GENERAL WEIGHTED SUM OF LNQD RANDOM VARIABLES AND ITS APPLICATION

  • KIM, HYUN-CHULL;KIM, TAE-SUNG
    • 대한수학회논문집
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    • 제20권3호
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    • pp.531-538
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    • 2005
  • In this paper we derive the central limit theorem for ${\sum}_{i=1}^n\;a_{ni}\xi_i$, where ${a_{ni},\;1\;{\leq}\;i\;{\leq}\;n}$ is a triangular array of nonnegative numbers such that $sup_n{\sum}_{i=1}^n\;a_{ni}^2\;<\;{\infty},\;max_{1{\leq}i{\leq}n}a_{ni}{\rightarrow}0\;as\;n\;{\rightarrow}\;{\infty}\;and\;\xi'_i\;s$ are a linearly negative quadrant dependent sequence. We also apply this result to consider a central limit theorem for a partial sum of a generalized linear process $X_n\;=\;\sum_{j=-\infty}^\infty\;a_k+_j{\xi}_j$.

A CENTRAL LIMIT THEOREM FOR GENERAL WEIGHTED SUMS OF LPQD RANDOM VARIABLES AND ITS APPLICATION

  • Ko, Mi-Hwa;Kim, Hyun-Chull;Kim, Tae-Sung
    • 대한수학회지
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    • 제43권3호
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    • pp.529-538
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    • 2006
  • In this paper we derive the central limit theorem for ${\sum}^n_{i=l}\;a_{ni}{\xi}_{i},\;where\;\{a_{ni},\;1\;{\le}\;i\;{\le}n\}$ is a triangular array of non-negative numbers such that $sup_n{\sum}^n_{i=l}\;a^2_{ni}\;<\;{\infty},\;max_{1{\le}i{\le}n\;a_{ni}{\to}\;0\;as\;n{\to}{\infty}\;and\;{\xi}'_{i}s$ are a linearly positive quadrant dependent sequence. We also apply this result to consider a central limit theorem for a partial sum of a generalized linear process of the form $X_n\;=\;{\sum}^{\infty}_{j=-{\infty}}a_{k+j}{\xi}_{j}$.

ON ALMOST SURE CONVERGENCE FOR WEIGHTED SUMS OF LNQD RANDOM VARIABLES

  • Choi, Jeong-Yeol;Kim, So-Youn;Baek, Jong-Il
    • 호남수학학술지
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    • 제34권2호
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    • pp.241-252
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    • 2012
  • Let $\{X_{ni},\;1{\leq}i{\leq}n,\;n{\geq}1\}$ be a sequence of LNQD which are dominated randomly by another random variable X. We obtain the complete convergence and almost sure convergence of weighted sums ${\sum}^n_{i=1}a_{ni}X_{ni}$ for LNQD by using a new exponential inequality, where $\{a_{ni},\;1{\leq}i{\leq}n,\;n{\geq}1\}$ is an array of constants. As corollary, the results of some authors are extended from i.i.d. case to not necessarily identically LNQD case.