• 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.

• Bulletin of the Korean Mathematical Society
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• v.52 no.3
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• pp.717-734
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• 2015

In this paper, we provide a classification of arithmetic functions in terms of identically-free-distributedness, determined by a fixed prime. We show then such classifications are free from the choice of primes. In particular, we obtain that the algebra $A_p$ of equivalence classes under the quotient on A by the identically-free-distributedness is isomorphic to an algebra $\mathbb{C}^2$, having its multiplication $({\bullet});(t_1,t_2){\bullet}(s_1,s_2)=(t_1s_1,t_1s_2+t_2s_1)$.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.