• Title/Summary/Keyword: identically distributed

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ON CHARACTERIZATIONS OF THE CONTINUOUS DISTRIBUTIONS BY INDEPENDENCE PROPERTY OF RECORD VALUES

  • JIN, HYUN-WOO;LEE, MIN-YOUNG
    • Journal of applied mathematics & informatics
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    • v.35 no.5_6
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    • pp.651-657
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    • 2017
  • A sequence {$X_n,\;n{\geq}1$} of independent and identically distributed random variables with absolutely continuous (with respect to Lebesque measure) cumulative distribution function F(x) is considered. We obtain two characterizations of a family of continuous probability distribution by independence property of record values.

On the Estimation of Reliability Functions for the Freund Model

  • Hong, Yeon-Woong;Lee, Jae-Man;Cha, Young-Joon
    • Journal of the Korean Data and Information Science Society
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    • v.8 no.1
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    • pp.79-83
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    • 1997
  • This paper considers the problem of estimating the model parameters and reliability functions for Freund bivariate exponential distribution. Uniformly minimum variance unbiased estimators for model parameters, joint reliability and marginal reliability functions are obtained in the both case of non-identically distributed marginals and identically distributed marginals.

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A CHARACTERIZATION OF GAMMA DISTRIBUTION BY INDEPENDENT PROPERTY

  • Lee, Min-Young;Lim, Eun-Hyuk
    • Journal of the Chungcheong Mathematical Society
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    • v.22 no.1
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    • pp.1-5
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    • 2009
  • Let {$X_n,\;n{\geq}1}$ be a sequence of independent identically distributed(i.i.d.) sequence of positive random variables with common absolutely continuous distribution function(cdf) F(x) and probability density function(pdf) f(x) and $E(X^2)<{\infty}$. The random variables $\frac{X_i{\cdot}X_j}{(\Sigma^n_{k=1}X_k)^{2}}$ and $\Sigma^n_{k=1}X_k$ are independent for $1{\leq}i if and only if {$X_n,\;n{\geq}1}$ have gamma distribution.

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A NOTE ON THE CHARACTERIZATIONS OF THE GUMBEL DISTRIBUTION BASED ON LOWER RECORD VALUES

  • Jin, Hyun-Woo;Lee, Min-Young
    • Journal of the Chungcheong Mathematical Society
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    • v.30 no.3
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    • pp.285-289
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    • 2017
  • Let $\{X_n,\;n{\geq}1\}$ be a sequence of independent and identically distributed random variables with cdf F(x) which is absolutely continuous with pdf f(x) and F(x) < 1 for all x in ($-{\infty},\;{\infty}$). In this paper, we obtain the characterizations of the Gumbel distribution by lower record values.

ON CHARACTERIZATIONS OF THE NORMAL DISTRIBUTION BY INDEPENDENCE PROPERTY

  • LEE, MIN-YOUNG
    • Journal of applied mathematics & informatics
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    • v.35 no.3_4
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    • pp.261-265
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    • 2017
  • Let X and Y be independent identically distributed nondegenerate random variables with common absolutely continuous probability distribution function F(x) and the corresponding probability density function f(x) and $E(X^2)$<${\infty}$. Put Z = max(X, Y) and W = min(X, Y). In this paper, it is proved that Z - W and Z + W or$(X-Y)^2$ and X + Y are independent if and only if X and Y have normal distribution.

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.

CONVERGENCE RATES FOR SEQUENCES OF CONDITIONALLY INDEPENDENT AND CONDITIONALLY IDENTICALLY DISTRIBUTED RANDOM VARIABLES

  • Yuan, De-Mei
    • Journal of the Korean Mathematical Society
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    • v.53 no.6
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    • pp.1275-1292
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    • 2016
  • The Marcinkiewicz-Zygmund strong law of large numbers for conditionally independent and conditionally identically distributed random variables is an existing, but merely qualitative result. In this paper, for the more general cases where the conditional order of moment belongs to (0, ${\infty}$) instead of (0, 2), we derive results on convergence rates which are quantitative ones in the sense that they tell us how fast convergence is obtained. Furthermore, some conditional probability inequalities are of independent interest.

Local Asymptotic Normality for Independent Not Identically Distributed Observations in Semiparametric Models

  • Park, Byeong U.;Jeon, Jong W.;Song, Moon S.;Kim, Woo C.
    • Journal of the Korean Statistical Society
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    • v.20 no.1
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    • pp.85-92
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    • 1991
  • A set of conditions ensuring local asymptotic normality for independent but not necessarily identically distributed observations in semiparametric models is presented here. The conditions are turned out to be more direct and easier to verify than those of Oosterhoff and van Zwet(1979) in semiparametric models. Examples considered include the simple linear regression model and Cox's proportional hazards model without censoring where the covariates are not random.

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Performance Analysis for Selection Decode-and-Forward Relay Networks with Differential Modulation over Rayleigh Fading Channels (레일리 페이딩 채널에서 차등 변조기법을 이용한 선택적 복호 후 재전송 중계 네트워크의 성능 분석)

  • Kong, Hyung-Yun;Bao, Vo Nguyen Quoc
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.1A
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    • pp.1-9
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    • 2010
  • This paper offers performance analysis of selection decode and forward (DF) networks with differential modulation/demodulation for an arbitrary number of relays in independent but not identically distributed Rayleigh fading channels. We have shown that the selection DF protocol with differential modulation can achieve full diversity in both independent identically distributed (i.i.d.) and independent but not identically distributed (i.n.d.) Rayleigh fading channels, and the performance loss due to using non-coherent detection is not substantial. Furthermore, we study the impact of combining techniques on the performance of the system by comparing a system that uses selection combining (SC) to one that uses maximum ratio combining (MRC). Simulations are performed and show that they match exactly with analytic ones in high SNR regime.

GENERALIZED CONVOLUTION OF UNIFORM DISTRIBUTIONS

  • Kang, Jong-Seong;Kim, Sung-Lai;Kim, Yang-Hee;Jang, Yu-Seon
    • Journal of applied mathematics & informatics
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    • v.28 no.5_6
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    • pp.1573-1581
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    • 2010
  • we investigate the n-fold convolution of the uniform distributions. First, we are concerned with the explicit distribution function of the partial sum ${\zeta}_n$ when the random variables are independent and has identically uniform distribution, next, we determine the n-fold convolution distribution of ${\zeta}_n$ when the identically distributed condition is not satisfied.