• Communications for Statistical Applications and Methods
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• v.15 no.5
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• pp.775-781
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• 2008

It is developed that a family of the semicircular Laplace distributions for modeling semicircular data by simple projection method. Mathematically it is simple to simulate observations from a semicircular Laplace distribution. We extend it to the l-axial Laplace distribution by a simple transformation for modeling any arc of arbitrary length. Similarly we develop the l-axial log-Laplace distribution based on the log-Laplace distribution. A bivariate version of l-axial Laplace distribution is also developed.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.127-130
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• 2003

주변분포가 Laplace 분포인 세 가지 형태의 이변량 Laplace 분포를 연구한다. 각각의 이변량 Laplace 분포의 확률밀도함수와 누적분포함수를 유도하고, 분포의 그래프를 그려봄으로써 분포의 형태를 알아본다. 조건부 적률을 정리하여 조건부 첨도와 조건부 왜도를 구하고 분포의 성질을 파악한다. 상관계수를 구하여 다른 이변량 분포의 상관계수와 비교해 보았다. 그리고 정의된 분포함수를 응용하여 이변량 Laplace 분포를 따르는 난수벡터를 발생하는 알고리즘을 제안하였으며, 생성된 난수벡터의 표본으로부터 구한 표본평균과 중앙값의 분산-공분산 행렬식을 구하고 이변량 정규분포에 대응하는 행렬식과 비교 토론하였다.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.243-250
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• 1999

We consider $Y=X{\lambda}Z,\;{\lambda}>0$, where X and Z are independent random variables, and Y is the length biased distribution or the equilibrium distribution of X. The purpose of this paper is to consider the distribution of X or Y when the distribution of Z is given and the distribution of Z when the distribution of X or Y is given, In particular, we obtain that the necessary and sufficient conditions for X to be $X^{2}({\upsilon})\;is\;Z{\sim}X^{2}(2)\;and\;for\;Z\;to\;be\;X^{2}(1)\;is\;X{\sim}IG({\mu},\;{\mu}^{2}/{\lambda})$, where $IG({\mu},\;{\mu}^{2}/{\lambda})$ is two-parameter inverse Gaussian distribution. Also we show that X is smaller than Y in the reverse Laplace transform ratio order if and only if $X_{e}$ is smaller than $Y_{e}$ in the Laplace transform ratio order. Finally, we can get the results that if X is smaller than Y in the Laplace transform ratio order, then $Y_{L}$ is smaller than $X_{L}$ in the Laplace transform order, and that if X is smaller than Y in the reverse Laplace transform ratio order, then $_{\mu}X_{L}$ is smaller than $_{\nu}Y_{L}$ in the Laplace transform order.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.573-584
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• 2007

We define a skew-symmetric Laplace distribution by a symmetric Laplace distribution and evaluate its coefficient of skewness. And we derive an approximate maximum likelihood estimator(AME) and a moment estimator(MME) of a skewed parameter in a skew-symmetric Laplace distribution, and hence compare simulated mean squared errors of those estimators. We compare asymptotic mean squared errors of two defined estimators of reliability in two independent skew-symmetric distributions.

• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.521-530
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• 1997

The new Laplace autoregressive model of order 2-NLAR92) studied by Dewald and Lewis (1985) is extended to the p-th order model-NLAR(p). A necessary and sufficient condition for the existence of an innovation sequence and a stationary ergodic NLAR(p) model is obtained. It is shown that the distribution of the innovation sequence is given by the probabilistic mixture of independent Laplace distributions and a degenrate distribution.

• Progress in Medical Physics
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• v.4 no.2
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• pp.37-47
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• 1993

The quality of radiation for a high energy x-ray beam can be specified by its attenuation curve in a selected material. The inverse Laplace transform of the attenuation curve can be used as an approximate indication of the energy spectrum of the beam. We have made a comparative investigation of the estimated spectrum obtained by the Laplace transform analysis of the transmitted exposure data measured in an absorption study of a 6MV x-ray beam. Two of existing transform pair models have been investicated and discussed.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.22 no.2
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• pp.125-136
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• 2018

In this article, a homotopy perturbation transform method (HPTM) and the Laplace transform combined with Taylor expansion method are presented for solving Volterra integral equations with a convolution kernel. The (HPTM) is innovative in Laplace transform algorithm and makes the calculation much simpler while in the Laplace transform and Taylor expansion method we first convert the integral equation to an algebraic equation using Laplace transform then we find its numerical inversion by power series. The numerical solution obtained by the proposed methods indicate that the approaches are easy computationally and its implementation very attractive. The methods are described and numerical examples are given to illustrate its accuracy and stability.

• Journal of the Korean Statistical Society
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• v.33 no.1
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• pp.107-128
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• 2004

Bivariate Laplace distributions for which both marginal distributions and Laplace are discussed. Three kinds of bivariate Laplace distributions which are extended bivariate exponential distributions of Gumbel (1960) are introduced in this paper. These symmetrical distributions are compared with asymmetrical distributions of Kotz et al. (2000). Their probability density functions, cumulative distribution functions are derived. Conditional skewnesses and kurtoses are also defined. Their correlation coefficients are calculated and compared with others. We proposed bivariate random vector generating methods whose distributions are bivariate Laplace. With sample means and medians obtained from generated random vectors, variance and covariance matrices of means and medians are calculated and discussed with those of bivariate normal distribution.

• Journal of the Korean Mathematical Society
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• v.55 no.6
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• pp.1435-1458
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• 2018

In this paper, we would like to give an answer to Problem 1 below issued firstly in [17]. In fact, by imposing some conditions on the mean curvature of the initial hypersurface and the coefficient function of the forcing term of a forced mean curvature flow considered here, we can obtain that the first eigenvalues of the Laplace and the p-Laplace operators are monotonic under this flow. Surprisingly, during this process, we get an interesting byproduct, that is, without any complicate constraint, we can give lower bounds for the first nonzero closed eigenvalue of the Laplacian provided additionally the second fundamental form of the initial hypersurface satisfies a pinching condition.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1171-1177
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• 2007

We consider estimation of the right-tail probability in a log-Laplace random variable, As we derive the density of ratio of two independent log-Laplace random variables, the k-th moment of the ratio is represented by a special mathematical function. and hence variance of the ratio can be represented by a psi-function.