• Title/Summary/Keyword: 파레토분포

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A Study on the Theory of Power-law and Science Technology Policy System under Convergence Technology Environment (융합기술환경에서 멱법칙과 과학기술정책체계분석)

  • Cho, Sang-Sup
    • Journal of Korea Technology Innovation Society
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    • v.15 no.1
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    • pp.28-46
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    • 2012
  • This paper proposes the science and technology policy implications of power law in econophysics methodology under the recent convergence technology environment. Empirical results are summarized as follow: first, similar empirical results are showed up using Hill estimates and Rank-1/2 estimates in patent data set during 1990 through 2008. Second, the estimates of power law exponents for technology capability distribution are decreased during the periods. The policy implications for science and technology development draw from the empirical results. First, the fact that the exponents of power law are decreased show the convergence of technology capability among countries. The our country policy directs focus on the innovation strategy rather than imitation strategy. Second, the volatility of technology change results from a few capable technology developers so that policy direct may need to control the technology power in the large technology developer or company. The methodology and analytical results used in the paper may also be useful for consider for the science and technology phenomena such as convergence and divergence of technologies among countries in the world.

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Efficient Inverter Type Compressor System using the Distribution of the Air Flow Rate (공기 변화량 분포를 이용한 효율적인 인버터타입 압축기 시스템)

  • Shim, JaeRyong;Kim, Yong-Chul;Noh, Young-Bin;Jung, Hoe-kyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.10
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    • pp.2396-2402
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    • 2015
  • Air compressor, as an essential equipment used in the factory and plant operations, accounts for around 30% of the total electricity consumption in U.S.A, thereby being proposed advanced technologies to reduce electricity consumption. When the fluctuation of the compressed airflow rate is small, the system stability is increased followed by the reduction of the electricity consumption which results in the efficient design of the energy system. In the statistical analysis, the normal distribution, log normal distribution, gamma distribution or the like are generally used to identify system characteristics. However a single distribution may not fit well the data with long tail, representing sudden air flow rate especially in extremes. In this paper, authors decouple the compressed airflow rate into two parts to present a mixture of distribution function and suggest a method to reduce the electricity consumption. This reduction stems from the fact that a general pareto distribution estimates more accurate quantile value than a gaussian distribution when an airflow rate exceeds over a large number.

Estimation of VaR and Expected Shortfall for Stock Returns (주식수익률의 VaR와 ES 추정: GARCH 모형과 GPD를 이용한 방법을 중심으로)

  • Kim, Ji-Hyun;Park, Hwa-Young
    • The Korean Journal of Applied Statistics
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    • v.23 no.4
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    • pp.651-668
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    • 2010
  • Various estimators of two risk measures of a specific financial portfolio, Value-at-Risk and Expected Shortfall, are compared for each case of 1-day and 10-day horizons. We use the Korea Composite Stock Price Index data of 20-year period including the year 2008 of the global financial crisis. Indexes of five foreign stock markets are also used for the empirical comparison study. The estimator considering both the heavy tail of loss distribution and the conditional heteroscedasticity of time series is of main concern, while other standard and new estimators are considered too. We investigate which estimator is best for the Korean stock market and which one shows the best overall performance.

Statistical frequency analysis of snow depth using mixed distributions (혼합분포함수를 적용한 최심신적설량에 대한 수문통계학적 빈도분석)

  • Park, Kyung Woon;Kim, Dongwook;Shin, Ji Yae;Kim, Tae-Woong
    • Journal of Korea Water Resources Association
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    • v.52 no.12
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    • pp.1001-1009
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    • 2019
  • Due to recent increasing heavy snow in Korea, the damage caused by heavy snow is also increasing. In Korea, there are many efforts including establishing disaster prevention measures to reduce the damage throughout the country, but it is difficult to establish the design criteria due to the characteristics of heavy snow. In this study, snowfall frequency analysis was performed to estimate design snow depths using observed snow depth data at Jinju, Changwon and Hapcheon stations. The conventional frequency analysis is sometime limted to apply to the snow depth data containing zero values which produce unrealistc estimates of distributon parameters. To overcome this problem, this study employed mixed distributions based on Lognormal, Generalized Pareto (GP), Generalized Extreme Value (GEV), Gamma, Gumbel and Weibull distribution. The results show that the mixed distributions produced smaller design snow depths than single distributions, which indicated that the mixed distributions are applicable and practical to estimate design snow depths.

A Analysis of Heavy Tailed Distribution for Files in Web Servers Using TTT Plot Technique (TTT 타점법을 이용한 웹서버 파일 분포의 후미성 분석)

  • Jung, Sung-Moo;Lee, Sang-Yong;Jang, Joong-Soon;Song, Jae-Shin;Yoo, Hae-Young;Choi, Kyung-Hee
    • The KIPS Transactions:PartA
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    • v.10A no.3
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    • pp.189-198
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    • 2003
  • In this paper, we propose a method of analysis to show the heavy-tailed statistical distribution of file sizes in web servers, using TTT plot technique. TTT plot technique, a well-known method in the area of reliability engineering, determines that a distribution of samples fellows a heavy tailed one when their TTT statistical plots are lied on a straight line. We performed an intensive simulation using data gathered from real web servers. The simulation indicates that the proposed method is superior to Hill estimation technique or LLCD plot method in efficiency of data analysis. Moreover, the proposed method eliminates the possible decision error, which Pareto distribution or traditional method might cause.

Prediction of Stream Flow on Probability Distributed Model using Multi-objective Function (다목적함수를 이용한 PDM 모형의 유량 분석)

  • Ahn, Sang-Eok;Lee, Hyo-Sang;Jeon, Min-Woo
    • Journal of the Korean Society of Hazard Mitigation
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    • v.9 no.5
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    • pp.93-102
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    • 2009
  • A prediction of streamflow based on multi-objective function is presented to check the performance of Probability Distributed Model(PDM) in Miho stream basin, Chungcheongbuk-do, Korea. PDM is a lumped conceptual rainfall runoff model which has been widely used for flood prevention activities in UK Environmental Agency. The Monte Carlo Analysis Toolkit(MCAT) is a numerical analysis tools based on population sampling, which allows evaluation of performance, identifiability, regional sensitivity and etc. PDM is calibrated for five model parameters by using MCAT. The results show that the performance of model parameters(cmax and k(q)) indicates high identifiability and the others obtain equifinality. In addition, the multi-objective function is applied to PDM for seeking suitable model parameters. The solution of the multi-objective function consists of the Pareto solution accounting to various trade-offs between the different objective functions considering properties of hydrograph. The result indicated the performance of model and simulated hydrograph are acceptable in terms on Nash Sutcliffe Effciency*(=0.035), FSB(=0.161), and FDBH(=0.809) to calibration periods, validation periods as well.

Estimation of the Gini Index Based on the Properties of Circle (원의 성질을 이용한 GINI INDEX의 추정)

  • 강석복;조영석
    • The Korean Journal of Applied Statistics
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    • v.16 no.2
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    • pp.283-291
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    • 2003
  • The Gini index is one of the most commonly used measures of inequality of income distributions. In this paper, the Lorenz curve is estimated by arcs of two optimal circles, and a new simple method to estimate the Gini index is proposed using the law of cosines. We compare the proposed estimator with the estimator proposed by Ogwang and Rao(1996) in terms of the mean squared error(MSE) though Monte Carlo simulation in a Pareto distribution.

Effect of Energy Saving and Delay on Burst Assemble and Traffic Pattern in OBS Networks with Sleeping Mode (수면 모드를 사용하는 OBS 망에서 트래픽 패턴 및 버스트 어셈블이 에너지 절감과 지연시간에 미치는 영향 분석)

  • Kang, Dong-Ki;Yang, Won-Hyuk;Lee, Jae-Young;Kim, Young-Chon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.2B
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    • pp.111-119
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    • 2011
  • As Green-IT has attracted a lot of attention in recent years, many researches have been interested in reducing the energy consumption of network equipments. In this paper, we analyze the energy saving ratio and delay performance according to various traffic patterns and burst assemble algorithms in OBS network with sleeping mode. To do this, we design the traffic generators, which are based on exponential distribution and Pareto distribution, and the router model, which has the time based and length based burst assemble algorithms by using OPNET modeler. Through OPNET simulator, we evaluate the energy saving performance in terms of the sleeping time, the number of transitions and packet delay.

Analysis of Extreme Values of Daily Percentage Increases and Decreases in Crude Oil Spot Prices (국제현물원유가의 일일 상승 및 하락율의 극단값 분석)

  • Yun, Seok-Hoon
    • The Korean Journal of Applied Statistics
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    • v.23 no.5
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    • pp.835-844
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    • 2010
  • Tools for statistical analysis of extreme values include the classical annual maximum method, the modern threshold method and variants improving the second one. While the annual maximum method is to t th generalized extreme value distribution to the annual maxima of a time series, the threshold method is to the generalized Pareto distribution to the excesses over a high threshold from the series. In this paper we deal with the Poisson-GPD method, a variant of the threshold method with a further assumption that the total number of exceedances follows the Poisson distribution, and apply it to the daily percentage increases and decreases computed from the spot prices of West Texas Intermediate, which were collected from January 4th, 1988 until December 31st, 2009. According to this analysis, the distribution of daily percentage increases as well as decreases turns out to have a heavy tail, unlike the normal distribution, which coincides well with the general phenomenon appearing in the analysis of lots of nowaday nancial data.

Time Series Modelling of Air Quality in Korea: Long Range Dependence or Changes in Mean? (한국의 미세먼지 시계열 분석: 장기종속 시계열 혹은 비정상 평균변화모형?)

  • Baek, Changryong
    • The Korean Journal of Applied Statistics
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    • v.26 no.6
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    • pp.987-998
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    • 2013
  • This paper considers the statistical characteristics on the air quality (PM10) of Korea collected hourly in 2011. PM10 in Korea exhibits very strong correlations even for higher lags, namely, long range dependence. It is power-law tailed in marginal distribution, and generalized Pareto distribution successfully captures the thicker tail than log-normal distribution. However, slowly decaying autocorrelations may confuse practitioners since a non-stationary model (such as changes in mean) can produce spurious long term correlations for finite samples. We conduct a statistical testing procedure to distinguish two models and argue that the high persistency can be explained by non-stationary changes in mean model rather than long range dependent time series models.