• Communications for Statistical Applications and Methods
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• 제26권6호
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• pp.583-589
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• 2019

Counterexamples of a skew-normal distribution are developed to improve our understanding of this distribution. Two examples on bivariate non-skew-normal distribution owning marginal skew-normal distributions are first provided. Sum of dependent skew-normal and normal variables does not follow a skew-normal distribution. Continuous bivariate density with discontinuous marginal density also exists in skew-normal distribution. An example presents that the range of possible correlations for bivariate skew-normal distribution is constrained in a relatively small set. For unified skew-normal variables, an example about converging in law are discussed. Convergence in distribution is involved in two separate examples for skew-normal variables. The point estimation problem, which is not a counterexample, is provided because of its importance in understanding the skew-normal distribution. These materials are useful for undergraduate and/or graduate teaching courses.

• Communications for Statistical Applications and Methods
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• 제11권2호
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• pp.265-274
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• 2004

The paper extends earlier work on the skew-normal distribution, a family of distributions including normal, but with extra parameter to regulate skewness. The present work introduces a singly truncated parametric family that strictly includes a truncated normal distribution, and studies its properties, with special emphasis on the relation with bivariate normal distribution.

• Journal of the Korean Data and Information Science Society
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• 제16권2호
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• pp.451-456
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• 2005

We introduce the standard two-sided power normal distribution and consider the relation between the probability in standard two-sided power distribution and the probability in standard two-sided power normal distribution and obtain the even moment of the special two-sided power normal distribution including the cases considered by Gupta and Nadarajah(2004)

• Communications for Statistical Applications and Methods
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• 제15권2호
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• pp.161-171
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• 2008

This study discusses Johnson's $S_U$-normal distribution capturing a wide range of non-normality in various regression models. We provide the likelihood inference using Johnson's $S_U$-normal distribution, and propose a likelihood ratio (LR) test for normality. We also apply the $S_U$-normal distribution to the binary and censored regression models. Monte Carlo simulations are used to show that the LR test using the $S_U$-normal distribution can be served as a model specification test for normal error distribution, and that the $S_U$-normal maximum likelihood (ML) estimators tend to yield more reliable marginal effect estimates in the binary and censored model when the error distributions are non-normal.

• 해양환경안전학회지
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• 제21권3호
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• pp.253-258
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• 2015

The purpose of this study is to find suitable probability distribution function of complex distribution data like multimodal. Normal distribution is broadly used to assume probability distribution function. However, complex distribution data like multimodal are very hard to be estimated by using normal distribution function only, and there might be errors when other distribution functions including normal distribution function are used. In this study, we experimented to find fit probability distribution function in multimodal area, by using AIS(Automatic Identification System) observation data gathered in Mokpo port for a year of 2013. By using chi-squared statistic, gaussian mixture model(GMM) is the fittest model rather than other distribution functions, such as extreme value, generalized extreme value, logistic, and normal distribution. GMM was found to the fit model regard to multimodal data of maritime traffic flow distribution. Probability density function for collision probability and traffic flow distribution will be calculated much precisely in the future.

• Communications for Statistical Applications and Methods
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• 제31권1호
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• pp.129-142
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• 2024

In various industries, especially manufacturing and chemical industries, it is often observed that the distribution of a specific process, initially having followed a normal distribution, becomes skewed as a result of unexpected causes. That is, a process deviates from a normal distribution and becomes a skewed distribution. The skew-normal (SN) distribution is one of the most employed models to characterize such processes. The shape of this distribution is determined by the asymmetry parameter. When this parameter is set to zero, the distribution is equal to the normal distribution. Moreover, when there is a shift in the asymmetry parameter, the mean and variance of a SN distribution shift accordingly. In this paper, we propose procedures for monitoring the asymmetry parameter, based on the statistic derived from the noncentral t-distribution. After applying the statistic to Shewhart and the exponentially weighted moving average (EWMA) charts, we evaluate the performance of the proposed procedures and compare it with previously studied procedures based on other skewness statistics.

• 한국수학교육학회지시리즈E:수학교육논문집
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• 제24권1호
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• pp.177-193
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• 2010

본 연구는 고등학교 통계 영역의 확률분포에 제시되어 있는 정규분포를 이항분포에서 정규분포로의 근사, 정규분포곡선의 탐구, Monte Carlo 방법에 의한 정규분포곡선의 넓이 탐구, 정규분포곡선의 선형변환, 그리고 여러 형태의 정규분포곡선 탐구 등의 내용을 중심으로 CAS 계산기를 활용하여 탐구해보고자 한다. CAS 계산기의 도구적 기능인 사소화, 실험, 시각화, 집중의 측면에서 볼 때 지필로서는 교육과정에 제시된 확률분포의 목표를 달성하기 불가능하다고 판단된다. 따라서 본 연구에서는 CAS 계산기를 활용하여 정규분포곡선의 다양한 성질을 탐구하고 이러한 과정과 결과로부터 정규분포곡선에 대한 교수학적 시사점을 도출하고자 한다.

• 환경영향평가
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• 제23권4호
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• pp.285-295
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• 2014

본 연구는 논으로부터 배출되는 오염물질항목별(COD, TOC, T-N, T-P, SS) 농도 분포에 적합한 확률분포모형을 분석하고 실측 평균 EMC와 확률분포 모형을 통해 추정된 중앙값 EMC(EMC50)값과 비교하였다. 이를 위해 2008년부터 2011년까지 전라남도 함평군에 위치한 논에서 모니터링을 수행하였다. 그 결과 COD는 3가지 확률분포모형(Normal, Log-Normal, Gamma), T-N은 4가지 확률분포모형(Normal, Log-Normal, Gamma, Weibull), T-P와 TOC는 3가 지 확 률 분 포 모 형 (Log-Normal, Gamma, Weibull), SS는 2가지 확률분포모형 (Log-Normal, Gamma)에서 적합한 것으로 나타났다. 특히, Log-Normal과 Gamma 확률분포모형은 모든 수질항목에 적합한 확률분포모형인 것으로 나타났다. 한편, 강우시 논 유출수의 수질항목별 평균값과 확률분포모형을 통해 추정된 EMC 중앙값과 비교한 결과 COD는 Gamma, TOC, T-N, T-P, SS는 Log-Normal 확률분포모형의 값과 비슷하게 나타났다.

• 대한수학교육학회지:수학교육학연구
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• 제22권2호
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• pp.117-136
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• 2012

이 연구는 정규분포에 대한 교수학적 변환 방식과 학생들의 이해의 특징을 분석함으로써 고등학교 통계 단원에서 정규분포를 지도하는 것과 관련된 시사점을 얻는데 목적을 두었다. 이를 위해 정규분포의 역사 발생 과정과 학문적 지식으로서 정규분포의 의미를 확인하여 정규분포의 교수학적 변환 방식을 살펴보기 위한 4개의 분석 관점을 추출하고 이를 토대로 미국, 영국, 우리나라 교과서의 정규분포에 대한 교수학적 변환 방식을 분석하였다. 또한 정규분포에 대한 학생들의 이해 특징과 관련된 선행 연구 결과를 살펴봄으로써 고등학생들의 정규분포에 대한 이해의 특징을 기술하는데 필요한 분석 관점을 4가지로 구체화하였으며, 이를 토대로 분석한 학생들의 이해 특징을 4가지로 요약하였다.

• 한국물환경학회지
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• 제25권3호
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• pp.425-431
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• 2009

It is very important to know the probability distribution of water-quality constituents for water-quality control and management of rivers and reservoirs effectively. The probability distribution of BOD in Anseong Stream was analyzed in this paper using Kolmogorov-Smirnov test which is widely used goodness-of-fit method. It was known that the distribution of BOD in Anseong Stream is closer to Log-normal, Gamma and Weibull distributions than Normal distribution. Normal distribution can be partially applied depending on significance level, but Log-normal, Gamma and Weibull distributions can be used in any significance level. Also the estimated Log-normal distribution of BOD at Jinwi3 station was to be compared with the measured in 2001, 2002 and 2003 years. It was revealed that the estimated probability distribution of BOD at Jinwi3 follows a theoretical distribution very well. The applicable probability distribution of BOD can be used to explain more rigorously and scientifically the achievement or violation of target concentration in TMDL(Total Maximum Daily Load).