• Journal of the Korean Statistical Society
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• 제36권1호
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• pp.111-127
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• 2007

The logistic distribution is generalized using the Marshall-Olkin scheme and its generalization. Some properties are studied. First order autoregressive time series model with Marshall-Olkin semi-logistic distribution as marginal is developed and studied.

• 한국농공학회지
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• 제44권6호
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• pp.49-60
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• 2002

This study was conducted to estimate the design flood by the determination of best fitting order of LH-moments of the annual maximum series at six and nine watersheds in Korea and Australia, respectively. Adequacy for flood flow data was confirmed by the tests of independence, homogeneity, and outliers. Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Pareto (GPA), and Generalized Logistic (GLO) distributions were applied to get the best fitting frequency distribution for flood flow data. Theoretical bases of L, L1, L2, L3 and L4-moments were derived to estimate the parameters of 4 distributions. L, L1, L2, L3 and L4-moment ratio diagrams (LH-moments ratio diagram) were developed in this study. GEV distribution for the flood flow data of the applied watersheds was confirmed as the best one among others by the LH-moments ratio diagram and Kolmogorov-Smirnov test. Best fitting order of LH-moments will be derived by the confidence analysis of estimated design flood in the second report of this study.

• 대한수학회논문집
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• 제36권4호
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• pp.671-684
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• 2021

The tenacity of the current paper is to find connections between various subclasses of analytic univalent functions by applying certain convolution operator involving generalized hypergeometric distribution series. To be more specific, we examine such connections with the classes of analytic univalent functions k - 𝓤𝓒𝓥^* (𝛽), k - 𝓢^*_p (𝛽), 𝓡 (𝛽), 𝓡^𝜏 (A, B), k - 𝓟𝓤𝓒𝓥^* (𝛽) and k - 𝓟𝓢^*_p (𝛽) in the open unit disc 𝕌.

• Communications for Statistical Applications and Methods
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• 제3권2호
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• pp.249-273
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• 1996

This paper reviews and develops several statistical models for extreme values, based on threshold methodology. Extreme values of a time series are modeled in terms of tails which are defined as truncated forms of original variables, and Markov property is imposed on the tails. Tails of the generalized extreme value distribution and a multivariate extreme value distributively, of the tails of the series. These models are then applied to real ozone data series collected in the Chicago area. A major concern is given to detecting any possible trend in the extreme values.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2002년도 학술발표회 발표논문집
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• pp.229-232
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• 2002

This study was conducted to estimate the design flood by the determination of best fitting order of LH-moments of the annual maximum series at six and nine watersheds in Korea and Australia, respectively. Adequacy for flood flow data was confirmed by the tests of independence, homogeneity, and outliers. Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Pareto (GPA), and Generalized Logistic (GLO) distributions were applied to get the best fitting frequency distribution for flood flow data. Theoretical bases of L, L1, L2, L3 and L4-moments were derived to estimate the parameters of 4 distributions. L, L1, L2, L3 and L4-moment ratio diagrams (LH-moments ratio diagram) were developed in this study.

• 한국산학기술학회논문지
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• 제10권5호
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• pp.1009-1019
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• 2009

본 연구에서는 우리나라 수위관측소들 중에서 관측 유량이 검증된 총 19개 유역을 선정하고 관측된 홍수량을 사용하여 적정 설계홍수량을 유도함으로써 우리나라의 설계홍수량 특성을 분석하였다. 대상유역별로 관측개시 년도에서부터 분석 시작년을 기준으로 1년씩 증가 시키는 점진적 구성 방식으로 연최대홍수량에 대한 빈도분석을 실시하기 위해, 변동특성을 이동평균법에 의해 분석하였다. 19개 대상유역에 대한 연최대홍수량 계열 구성기간별로 기본통치를 산정하고 독립성, 동질성 및 Outiler 검정을 실시하였다. Gumbel, Generalized Extreme Value, Generalized Logistic 및 Generalized Pareto 분포의 적합도 검정을 LH-모멘트비도와 Kolmogorov-Smirnov 검정에 의해 수행하였다. 적정 확률분포로 선정된 GEV 분포의 매개변수를 확률가중모멘트의 치수 변화에 의한 L, L1, L2, L3 및 L4-모멘트법에 의해 추정하고 대상유역 및 연최대홍수량 계열 구성 기간별 설계홍수량을 유도하였다. 본 연구에서 사용한 변동률 분석에 따라 최근 지구온난화에 따른 우리나라 기후 변화를 고려한 적절한 수리구조물의 설계 조건변경시기는 2002년 전후로 하여야 할 것이다.

• 한국농공학회지
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• 제39권3호
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• pp.83-95
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• 1997

This study was conducted to derive optimal design floods by Gamma distribution models of the annual maximum series at eight watersheds along Geum , Yeong San and Seom Jin river Systems, Design floods obtained by different methods for evaluation of parameters and for plotting positions in the Gamma distribution models were compared by the relative mean errors and graphical fit along with 95% confidence interval plotted on Gamma probability paper. The results were analyzed and summarized as follows. 1.Adequacy for the analysis of flood flow data used in this study was confirmed by the tests of Independence, Homogeneity and detection of Outliers. 2.Basic statistics and parameters were calculated by Gamma distribution models using Methods of Moments and Maximum Likelihood. 3.It was found that design floods derived by the method of maximum likelihood and Hazen plotting position formular of two parameter Gamma distribution are much closer to those of the observed data in comparison with those obtained by other methods for parameters and for plotting positions from the viewpoint of relative mean errors. 4.Reliability of derived design floods by both maximum likelihood and method of moments with two parameter Gamma distribution was acknowledged within 95% confidence interval.

• Wind and Structures
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• 제14권4호
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• pp.337-357
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• 2011

The collection of wind speed time series by means of digital data loggers occurs in many domains, including civil engineering, environmental sciences and wind turbine technology. Since averaging intervals are often significantly larger than typical system time scales, the information lost has to be recovered in order to reconstruct the true dynamics of the system. In the present work we present a simple algorithm capable of generating a real-time wind speed time series from data logger records containing the average, maximum, and minimum values of the wind speed in a fixed interval, as well as the standard deviation. The signal is generated from a generalized random Fourier series. The spectrum can be matched to any desired theoretical or measured frequency distribution. Extreme values are specified through a postprocessing step based on the concept of constrained simulation. Applications of the algorithm to 10-min wind speed records logged at a test site at 60 m height above the ground show that the recorded 10-min values can be reproduced by the simulated time series to a high degree of accuracy.

• 응용통계연구
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• 제23권5호
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• pp.835-844
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• 2010

극단값 통계 분석의 도구로는 전통적인 연간 최대값 방법과 현대적인 분계점 방법, 그리고 분계점 방법을 개선한 변형체 등으로 분류할 수 있다. 연간 최대값 방법은 시계열자료의 연간 최대값들에 대하여 일반화극단값분포를 적합시키는 것이고, 분계점 방법은 충분히 큰 하나의 분계점을 넘어서는 초과값들의 초과여분들에 대하여 일반화파레토분포를 적합시키는 것이다. 분계점 방법의 한 변형체로서 본 논문에서는 분계점 방법에 추가적으로 초과값들의 전체 개수가 포아송분포를 따른다고 가정하는 포아송-GPD 방법을 다루고, 이를 1988.01.04부터 2009.12.31까지 수집된 서부텍사스산중질유의 현물가격 자료로부터 계산된 일일 상승율과 일일 하락율에 적용한다. 이에 따르면 일일 상승율과 일일 하락율의 분포는 정규분포와 달리 두터운 꼬리를 갖는 분포로 나타났는데, 이는 오늘날의 많은 금융 자료분석에서 나타나는 일반적인 현상과 잘 부합하는 것이다.

• Wind and Structures
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• 제26권3호
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• pp.129-146
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• 2018

Extreme wind speed analysis has been carried out conventionally by assuming the extreme series data is stationary. However, time-varying trends of the extreme wind speed series could be detected at many surface meteorological stations in China. Two main reasons, exposure change and climate change, were provided to explain the temporal trends of daily maximum wind speed and annual maximum wind speed series data, recorded at Hangzhou (China) meteorological station. After making a correction on wind speed series for time varying exposure, it is necessary to perform non-stationary statistical modeling on the corrected extreme wind speed data series in addition to the classical extreme value analysis. The generalized extreme value (GEV) distribution with time-dependent location and scale parameters was selected as a non-stationary model to describe the corrected extreme wind speed series. The obtained non-stationary extreme value models were then used to estimate the non-stationary extreme wind speed quantiles with various mean recurrence intervals (MRIs) considering changing climate, and compared to the corresponding stationary ones with various MRIs for the Hangzhou area in China. The results indicate that the non-stationary property or dependence of extreme wind speed data should be carefully evaluated and reflected in the determination of design wind speeds.