• 대기
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• 제26권4호
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• pp.697-709
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• 2016

This study estimates and evaluates the extreme value of 30 m-resolution daily maximum and minimum temperatures over South Korea, using inverse distance weighting (IDW), parameter-elevation regression on independent slopes model (PRISM) and generalized extreme value (GEV) method. The three experiments are designed and performed to find the optimal estimation strategy to obtain extreme value. First experiment (EXP1) applies GEV firstly to automated surface observing system (ASOS) to estimate extreme value and then applies IDW to produce high-resolution extreme values. Second experiment (EXP2) is same as EXP1, but using PRISM to make the high-resolution extreme value instead of IDW. Third experiment (EXP3) firstly applies PRISM to ASOS to produce the high-resolution temperature field, and then applies GEV method to make high resolution extreme value data. By comparing these 3 experiments with extreme values obtained from observation data, we find that EXP3 shows the best performance to estimate extreme values of maximum and minimum temperatures, followed by EXP1 and EXP2. It is revealed that EXP1 and EXP2 have a limitation to estimate the extreme value at each grid point correctly because the extreme values of these experiments with 30 m-resolution are calculated from only 60 extreme values obtained from ASOS. On the other hand, the extreme value of EXP3 is similar to observation compared to others, since EXP3 produces 30m-resolution daily temperature through PRISM, and then applies GEV to that result at each grid point. This result indicates that the quality of statistically produced high-resolution extreme values which are estimated from observation data is different depending on the combination and procedure order of statistical methods.

• 재무관리연구
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• 제22권1호
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• pp.119-146
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• 2005

본 연구는 극한치 이론을 적용하여 국내 주식시장에 대한 VAR값을 구하고 이의 유용성을 살펴보았다. 극한치모형으로는 블록최대값모형과 POT 모형을 이용하였고 백테스트를 통하여 이들 모형의 적정성을 알아보았다. 극한치모형 중 블록최대값 모형은 신뢰수준의 변화에 따라 VAR 추정치의 변동이 매우 큰 것으로 나타났으며, 블록의 크기를 어떻게 선택하는가에 따라 모수의 추정치가 크게 달라져 VAR값의 안정성이 떨어지는 것으로 나타났다. 이는 국내 주식시장에 대해 VAR 측정시 블록최대값 모형을 사용하는 것은 적절치 않음을 시사하는 것이다. 반면 POT모형은 임계치의 선택에 따라서 VAR 값이 달라지기는 하나 상대적으로 안정적인 모습을 보이며, 또한 백테스트 결과 97.5% 이상의 신뢰수준에서 VAR값이 델타 VAR에 비하여 우수한 성과를 보이는 것으로 나타났다. 특히 POT모형은 신뢰수준이 높아질수록 그 우월성이 높은 것으로 나타나, 주로 99% 이상의 높은 신뢰수준의 VAR값을 이용하는 경우에 위험의 관리수단으로 유용한 모형임을 시사하고 있다. 또한 극한치모형은 수익률의 왼쪽 꼬리와 오른쪽 꼬리를 분리하여 추정하고 이를 VAR의 계산에 이용하기 때문에, 수익률분포가 비대칭적 특징을 보이는 우리나라 주식시장의 VAR 측정시 적절한 방법임을 확인할 수 있었다.

• Wind and Structures
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• 제1권1호
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• pp.25-42
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• 1998

Improvements to the Gumbel method of extreme value analysis of wind data made over the last two decades are reviewed and illustrated using sample data for Jersey. A new procedure for extending the Gumbel method to include M-th highest annual extremes is shown to be less effective than the standard method, but leads to a method for calibrating peak-over-threshold methods against the standard Gumbel approach. Peak-over-threshold methods that include at least the 3rd highest annual extremes, specifically the modified Jensen and Franck method and the "Method of independent storms" are shown to give the best estimates of extremes from observations.

• 한국해안해양공학회지
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• 제4권4호
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• pp.250-260
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• 1992

본 논문에서는 비교적 장기간의 조위 관측자료가 축적되어 있는 인천, 제주, 여수, 부산, 묵호에 대하여 극치확률법과 결합확률법을 이용하여 극치해면을 산정하였다. 극치확률법의 분포는 Gumbel, Weibull 및 일반화 극치(GEV)분포에 대하여 최소자승법, 모멘트법, 확률가중적률(PWM)법으로 parameter를 추정하여 극치해면을 산출하였다. 그 결과 Gumbel 분포와 최소자승법이 각각 다른 분포와 다른 parameter 추정법에 비해 크게 추정되는 경향이 있다. 그리고 결합확률법이 극치확률법 보다 대략 5-l0cm 정도 크게 나타났다. 이는 극치확률법이 tide와 surge가 동시에 발생한 조위를 사용한 반면 결합확률법은 동시 발생하지 않은 극치 tide와 극치 surge도 포함하여 극치해면을 산출하기 때문에 값이 조금 크게 추정된다.

• 응용통계연구
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• 제27권4호
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• pp.655-665
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• 2014

폭염, 폭우와 가뭄 등과 같은 이상 기후 현상에 대한 적절한 대응이 최근 많이 요구되고 있다. 이상 기후 현상을 분석하기 위해 극단값 분석 기법을 적용할 수 있는데, 본 논문은에서는 한국의 여름철 강수량 자료(1973년부터 2012년까지의 5월부터 9월)를 분계점 초과값 모형으로 분석해보았다. 분계점은 한국의 기상관측소들을 5개의 군집으로 나누어, 각 군집별로 지리 정보와 시간을 공변량으로 하는 분위수 회귀 방법을 통하여 추정하였다. Northrop과 Jonathan (2011)과 같이 극단값들이 시공간적으로 독립이라고 가정하고 분석한 후, 추정오차와 검정 과정에 공간 종속성을 반영하였다.

• 응용통계연구
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• 제25권5호
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• pp.757-773
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• 2012

Traditional value at risk(S-VaR) has a difficulity in predicting the future risk of financial asset prices since S-VaR is a backward looking measure based on the historical data of the underlying asset prices. In order to resolve the deficiency of S-VaR, an economic value at risk(E-VaR) using the risk neutral probability distributions is suggested since E-VaR is a forward looking measure based on the option price data. In this study E-VaR is estimated by assuming the generalized gamma distribution(GGD) as risk neutral density function which is implied in the option. The estimated E-VaR with GGD was compared with E-VaR estimates under the Black-Scholes model, two-lognormal mixture distribution, generalized extreme value distribution and S-VaR estimates under the normal distribution and GARCH(1, 1) model, respectively. The option market data of the KOSPI 200 index are used in order to compare the performances of the above VaR estimates. The results of the empirical analysis show that GGD seems to have a tendency to estimate VaR conservatively; however, GGD is superior to other models in the overall sense.

• Wind and Structures
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• 제16권4호
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• pp.355-372
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• 2013

The Gringorten estimator has been extensively used in extreme value analysis of wind speed records to obtain unbiased estimates of design wind speeds. This paper reviews the derivation of the Gringorten estimator for the mean plotting position of extremes drawn from parents of the exponential type and demonstrates how it eliminates most of the bias caused by the classical Weibull estimator. It is shown that the coefficients in the Gringorten estimator are the asymptotic values for infinite sample sizes, whereas the estimator is most often used for small sample sizes. The principles used by Gringorten are used to derive a new Consistent Linear Unbiased Estimator (CLUE) for the mean plotting positions for the Fisher Tippett Type 1, Exponential and Weibull distributions and for the associated standard deviations. Analytical and Bootstrap methods are used to calibrate the bias error in each of the estimators and to show that the CLUE are accurate to better than 1%.

• Wind and Structures
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• 제3권3호
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• pp.143-158
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• 2000

This report presents the findings of a one-year monitoring effort to empirically characterize and evaluate the nature of near-ground winds for structural engineering purposes. The current wind engineering practice in the United States does not explicitly consider certain important near-ground wind characteristics in typical rough terrain conditions and the possible effect on efficient design of low-rise structures, such as homes and other light-frame buildings that comprise most of the building population. Therefore, near ground wind data was collected for the purpose of comparing actual near-ground wind characteristics to the current U.S. wind engineering practice. The study provides data depicting variability of wind speeds, wind velocity profiles for a major thunderstorm event and a northeaster, and the influence of thunderstorms on annual extreme wind speeds at various heights above ground in a typical rough environment. Data showing the decrease in the power law exponent with increasing wind speed is also presented. It is demonstrated that near-ground wind speeds (i.e., less than 10 m above ground) are likely to be over-estimated in the current design practice by as much as 20 percent which may result in wind load over-estimate of about 50% for low-rise buildings in typical rough terrain. The importance of thunderstorm wind profiles on determination of design wind speeds and building loads (particularly for buildings substantially taller than 10 m) is also discussed. Recommendations are given for possible improvements to the current design practice in the United States with respect to low-rise buildings in rough terrain and for the need to study the impact of thunderstorm gust profile shapes on extreme value wind speed estimates and building loads.

• Earthquakes and Structures
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• 제14권5호
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• pp.477-492
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• 2018

Recently, the adaptive nonlinear static analysis method has been widely used in the field of performance based earthquake engineering. However, the proposed methods are almost deterministic and cannot directly consider the seismic record uncertainties. In the current study an innovative Stochastic Adaptive Pushover Analysis, called "SAPA", based on equivalent hysteresis system responses is developed to consider the earthquake record to record uncertainties. The methodology offers a direct stochastic analysis which estimates the seismic demands of the structure in a probabilistic manner. In this procedure by using a stochastic linearization technique in each step, the equivalent hysteresis system is analyzed and the probabilistic characteristics of the result are obtained by which the lateral force pattern is extracted and the actual structure is pushed. To compare the results, three different types of analysis have been considered; conventional pushover methods, incremental dynamic analysis, IDA, and the SAPA method. The result shows an admirable accuracy in predicting the structure responses.

• Ocean Systems Engineering
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• 제7권4호
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• pp.345-369
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• 2017

The ocean environment offshore West Africa is considered to be mild. However, the generated swell from distant North and South Atlantic during austral winter and summer can reach high wave amplitudes with relatively low wave periods or low wave amplitudes with long wave periods, the later can be a crucial scenario to consider when the assessment of vessel resonance is of importance. Most offshore operations, which include offshore drilling, and installation in West Africa, are carried out from floating systems. The response of these systems and performance are governed by characteristics, such as amplitude and frequency of the wave and swell seas. It is therefore important to fully understand the sea conditions offshore Nigeria. This study covers the description of the swell sea offshore Nigeria using Bonga offshore wave measurements collected from the directional wave-rider (DWR), positioned at the Bonga site off the coast of Nigeria.