• Communications for Statistical Applications and Methods
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• 제2권2호
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• pp.347-349
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• 1995

In this paper a central limit theorem on $L^P(R)$ for $1{\leq}p<{\infty}$ is obtained with an example when ${X_n}$ is a sequence of independent, identically distributed random variables on $L^P(R)$.

• 응용통계연구
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• 제25권5호
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• pp.793-802
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• 2012

One proposal is made to construct a nonparametric estimator of slope parameters in a regression model under symmetric error distributions. This estimator is based on the use of the idea of minimizing approximate variance of a proposed estimator using regression quantiles. This nonparametric estimator and some other L-estimators are studied and compared with well known M-estimators through a simulation study.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제11권2호
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• pp.3-8
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• 2007

In this paper a generalized parametric mean length $L(P^{\nu},\;R)$ has been defined and bounds for $L(P^{\nu},\;R)$ are obtained in terms of generalized R-norm information measure.

• Communications for Statistical Applications and Methods
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• 제16권4호
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• pp.647-658
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• 2009

It is already known from the previous study that flood seems to have heavier tail. Therefore, to make prediction of future extreme label, some agreement of tail behavior of extreme data is highly required. The LH-moments estimation method, the generalized form of L-moments is an useful method of characterizing the upper part of the distribution. LH-moments are based on linear combination of higher order statistics. In this study, we have formulated LH-moments of five distributions useful in hydrology such as, two types of three parameter kappa distributions, beta-${\kappa}$ distribution, beta-p distribution and a generalized Gumbel distribution. Using LH-moments reduces the undue influences that small sample may have on the estimation of large return period events.

• Kyungpook Mathematical Journal
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• 제30권1호
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• pp.87-93
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• 1990

• Journal of the Korean Statistical Society
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• 제23권1호
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• pp.39-51
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• 1994

Some exponential moment inequalities for sub-gaussian random variables are studied in this paper. These inequalities are used to obtain laws of large numbers for random variable and random elements in $L^1(R)$.

• 한국멀티미디어학회논문지
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• 제12권1호
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• pp.26-30
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• 2009

본 논문에서는 로버스트 통계학의 순위 추정을 기반으로 하고 순서통계학의 L-추정자를 이용한 적응 순환 최소 순위(RLR) L-필터를 제안한다. 제안한 RLR-L 필터는 비선형 적응알고리즘을 가진 비선형 적응 필터로서 오차의 분산측정을 최소화하는 관점의 최적 필터로 가변적인 스텝 크기를 가지며 적응한다. 제안한 필터는 영상신호와 같은 비정체 신호나 가우시안 잡음 또는 임펄스 잡음과 같은 비선형 채널에 적합하다.

• Journal of the Korean Data and Information Science Society
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• 제28권6호
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• pp.1271-1278
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• 2017

Although the $L_0$-penalty is the most natural choice to identify the sparsity structure of the model, it has not been widely used due to the computational bottleneck. Recently, the adaptive ridge procedure is developed to efficiently approximate a $L_q$-penalized problem to an iterative $L_2$-penalized one. In this article, we proposed to apply the adaptive ridge procedure to solve the $L_0$-penalized weighted support vector machine (WSVM) to facilitate the corresponding optimization. Our numerical investigation shows the advantageous performance of the $L_0$-penalized WSVM compared to the conventional WSVM with $L_2$ penalty for both simulated and real data sets.

• Journal of the Korean Data and Information Science Society
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• 제27권4호
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• pp.1001-1012
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• 2016

대기오염물질이 인간의 건강에 악영향을 미치는 사실은 잘 알려져 있다. 유엔 환경 계획 (united nations environment program; UNEP) 보고서에 따르면, 미세먼지와 일산화탄소 오염물질로 연간 전 세계에서 430만 명이 목숨을 잃었다. 일산화탄소는 탄소와 산소로 구성된 화합물로 가정에서 생성되는 독성 가스 중 가장 위험한 가스이다. 연구를 위하여 2004년부터 2013년까지 10년간 대구 경북 지역의 대기오염관측소에서 관측된 1시간, 6시간, 12시간, 24시간 평균 일산화탄소 농도 자료를 사용하였다. 일반화 극단치 분포의 모수는 최우추정법과 L-적률추정법을 통해 추정하였고 적합도 검정을 수행하였다. 본 연구의 표본 수가 크지 않으므로 L-적률추정법이 최대우도법에 비해 모수추정에 적합하였다. 또한, 5년, 10년, 20년, 40년 재현수준을 추정하여 대구 경북 지역 일산화탄소 위험지역을 살펴보았다.

• 응용통계연구
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• 제22권1호
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• pp.205-220
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• 2009

For modeling skewed semicircular data, we derive new family of the exponential distributions. We extend it to the l-axial exponential distribution by a transformation for modeling any arc of arbitrary length. It is straightforward to generate samples from the f-axial exponential distribution. Asymptotic result reveals two things. The first is that linear exponential distribution can be used to approximate the l-axial exponential distribution. The second is that the l-axial exponential distribution has the asymptotic memoryless property though it doesn't have strict memoryless property. Some trigonometric moments are also derived in closed forms. Maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for goodness of fit test of the l-axial exponential distribution. We finally obtain a bivariate version of two kinds of the l-axial exponential distributions.