• 제목/요약/키워드: kernel distribution estimation

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비모수적 커널교정과 구간추정 (Nonparametric kernel calibration and interval estimation)

  • 이재창;전명식;김대학
    • 응용통계연구
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    • 제6권2호
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    • pp.227-235
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    • 1993
  • 순서쌍으로 주어진 자료 $(x_i, y_i), i=1,2,\cdots,n$ 들에 대한 독립변수와 관련된 추정은 회귀분석과는 달리 교정(calibration)이라고 불리워진다. 본 논문에서는 정규상 등과 같은 가정을 하지않고 비모수적인 커널방법을 이용하여 교정함수를 추정하고 추정된 교정함수의 붓스트랩 신뢰대를 이용한 독립변수의 구간추정을 제안하고자 한다. 교정과 커널방법에 대해 설명하였으며 독립변수의 추정에 대한 문헌적 고찰과 함께 붓스트랩 신뢰대에 대하여 첨언하였고 실제 자료를 통하여 다른방법과 비교, 분석하였다.

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Uncertainty analysis of containment dose rate for core damage assessment in nuclear power plants

  • Wu, Guohua;Tong, Jiejuan;Gao, Yan;Zhang, Liguo;Zhao, Yunfei
    • Nuclear Engineering and Technology
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    • 제50권5호
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    • pp.673-682
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    • 2018
  • One of the most widely used methods to estimate core damage during a nuclear power plant accident is containment radiation measurement. The evolution of severe accidents is extremely complex, leading to uncertainty in the containment dose rate (CDR). Therefore, it is difficult to accurately determine core damage. This study proposes to conduct uncertainty analysis of CDR for core damage assessment. First, based on source term estimation, the Monte Carlo (MC) and point-kernel integration methods were used to estimate the probability density function of the CDR under different extents of core damage in accident scenarios with late containment failure. Second, the results were verified by comparing the results of both methods. The point-kernel integration method results were more dispersed than the MC results, and the MC method was used for both quantitative and qualitative analyses. Quantitative analysis indicated a linear relationship, rather than the expected proportional relationship, between the CDR and core damage fraction. The CDR distribution obeyed a logarithmic normal distribution in accidents with a small break in containment, but not in accidents with a large break in containment. A possible application of our analysis is a real-time core damage estimation program based on the CDR.

ESTIMATION OF A MODIFIED INTEGRAL ASSOCIATED WITH A SPECIAL FUNCTION KERNEL OF FOX'S H-FUNCTION TYPE

  • Al-Omari, Shrideh Khalaf Qasem
    • 대한수학회논문집
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    • 제35권1호
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    • pp.125-136
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    • 2020
  • In this article, we discuss classes of generalized functions for certain modified integral operator of Bessel-type involving Fox's H-function kernel. We employ a known differentiation formula of Fox's H-function to obtain the definition and properties of the distributional modified Bessel-type integral. Further, we derive a smoothness theorem for its kernel in a complete countably multi-normed space. On the other hand, using an appropriate class of convolution products, we derive axioms and establish spaces of modified Boehmians which are generalized distributions. On the defined spaces, we introduce addition, convolution, differentiation and scalar multiplication and further properties of the extended integral.

커널 밀도 윈도우를 이용한 레이더 펄스 클러스터링 (Radar Pulse Clustering using Kernel Density Window)

  • 이동원;한진우;이원돈
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2008년도 하계종합학술대회
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    • pp.973-974
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    • 2008
  • As radar signal environments become denser and more complex, the capability of high-speed and accurate signal analysis is required for ES(Electronic warfare Support) system to identify individual radar signals at real-time. In this paper, we propose the new novel clustering algorithm of radar pulses to alleviate the load of signal analysis process and support reliable analysis. The proposed algorithm uses KDE(Kernel Density Estimation) and its CDF(Cumulative Distribution Function) to compose clusters considering the distribution characteristics of pulses. Simulation results show the good performance of the proposed clustering algorithm in clustering and classifying the emitters.

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비대칭 라플라스 분포를 이용한 분위수 회귀 (Quantile regression using asymmetric Laplace distribution)

  • 박혜정
    • Journal of the Korean Data and Information Science Society
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    • 제20권6호
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    • pp.1093-1101
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    • 2009
  • 분위수 회귀모형은 확률변수들 사이에 확률적인 관계구조를 포함한 함수 모형을 좀 더 완벽하게 추정하도록 제공한다. 본 논문에서는 함수 추정에 로버스트하다고 알려져 있는 서포트벡터기계 기법과 이중벌칙커널기계를 이용하여 분위수 회귀모형을 추정하고자 한다. 이중벌칙커널기계는 고차원의 입력변수에 대한 분위수 회귀가 요구될 때 분위수 회귀모형을 잘 추정한다고 알려져 있다. 또한 본 논문에서는 광범위한 형태의 분위수 회귀모형 추정을 위해서 정규분포보다 비대칭 라플라스 분포를 이용한다. 본 논문에서 제안한 모형은 분위수 회귀모형 추정을 위해서 서포트벡터기계 기법에 이중벌칙커널기계를 이용하여 각각의 평균과 분산을 동시에 추정한다. 평균과 분산함수 추정을 위해 사용된 커널함수의 모수들은 최적의 값을 찾기 위해 일반화근사 교차타당성을 이용한다.

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수질오염도의 공간적 분포 변화 분석 : 한강 유역을 대상으로 (Spatial Distribution of the Levels of Water Pollutants in Han River)

  • 김광수;권오상
    • 자원ㆍ환경경제연구
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    • 제18권1호
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    • pp.105-138
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    • 2009
  • 본 연구는 한강의 수질측정망에서 관측된 오염물질별 연평균 오염도를 이용하여 지난 15년 동안 수질오염도의 공간적 분포에 유의한 변화가 발생하였는지를 분석하였다. 구체적으로 각 오염물질별의 비모수적 커널확률밀도함수를 추정하였고, 연도간 유의한 변화가 있는지 검정하였다. 또한 일반화된 엔트로피 계열의 불평등지수를 구하고, 부트스트래핑 기법을 통해 불평등지수의 차이가 유의한지를 검정하였으며, 순위 상관을 이용하여 오염도 순위의 동태적인 측면을 분석하였다. 분석결과 최근 15년 동안 수질오염도의 불균등 정도는 전반적으로 완화되거나 일정한 수준을 유지하였고, 오염도 순위에 동태적인 변화는 거의 일어나지 않은 것으로 나타났다.

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글로벌 금융위기 이후 한국 주식유통시장의 위험가격에 관한 연구 (The Price of Risk in the Korean Stock Distribution Market after the Global Financial Crisis)

  • 손경우;유원석
    • 유통과학연구
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    • 제13권5호
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    • pp.71-82
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    • 2015
  • Purpose - The purpose of this study is to investigate risk price implied from the pricing kernel of Korean stock distribution market. Recently, it is considered that the quantitative easing programs of major developed countries are contributing to a reduction in global uncertainty caused by the 2007~2009 financial crisis. If true, the risk premium as compensation for global systemic risk or economic uncertainty should show a decrease. We examine whether the risk price in the Korean stock distribution market has declined in recent years, and attempt to provide practical implications for investors to manage their portfolios more efficiently, as well as academic implications. Research design, data and methodology - To estimate the risk price, we adopt a non-parametric method; the minimum norm pricing kernel method under the LOP (Law of One Price) constraint. For the estimation, we use 17 industry sorted portfolios provided by the KRX (Korea Exchange). Additionally, the monthly returns of the 17 industry sorted portfolios, from July 2000 to June 2014, are utilized as data samples. We set 120 months (10 years) as the estimation window, and estimate the risk prices from July 2010 to June 2014 by month. Moreover, we analyze correlation between any of the two industry portfolios within the 17 industry portfolios to suggest further economic implications of the risk price we estimate. Results - According to our results, the risk price in the Korean stock distribution market shows a decline over the period of July 2010 to June 2014 with statistical significance. During the period of the declining risk price, the average correlation level between any of the two industry portfolios also shows a decrease, whereas the standard deviation of the average correlation shows an increase. The results imply that the amount of systematic risk in the Korea stock distribution market has decreased, whereas the amount of industry-specific risk has increased. It is one of the well known empirical results that correlation and uncertainty are positively correlated, therefore, the declining correlation may be the result of decreased global economic uncertainty. Meanwhile, less asset correlation enables investors to build portfolios with less systematic risk, therefore the investors require lower risk premiums for the efficient portfolio, resulting in the declining risk price. Conclusions - Our results may provide evidence of reduction in global systemic risk or economic uncertainty in the Korean stock distribution market. However, to defend the argument, further analysis should be done. For instance, the change of global uncertainty could be measured with funding costs in the global money market; subsequently, the relation between global uncertainty and the price of risk might be directly observable. In addition, as time goes by, observations of the risk price could be extended, enabling us to confirm the relation between the global uncertainty and the effect of quantitative easing. These topics are beyond our scope here, therefore we reserve them for future research.

커널 밀도 추정을 이용한 Fuzzy C-Means의 초기화 (Initialization of Fuzzy C-Means Using Kernel Density Estimation)

  • 허경용;김광백
    • 한국정보통신학회논문지
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    • 제15권8호
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    • pp.1659-1664
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    • 2011
  • Fuzzy C-Means (FCM)는 군집화를 위해 널리 사용되는 알고리듬 중 하나로 다양한 응용 분야에서 성공적으로 사용되어 왔다. 하지만 FCM은 여러 가지 단점을 가지고 있으며 초기 원형 설정이 그 중 하나이다. FCM은 국부 최적해에 수렴하므로 초기 원형 설정에 따라 군집화의 결과가 달라진다. 따라서 초기 원형의 설정은 군집화 결과 향상을 위해 중요하다. 이 논문에서는 이러한 FCM의 초기 원형 설정 문제를 해결하는 방안으로 커널 밀도 추정을 활용하는 방법을 제안한다. 커널 밀도 추정은 비모수적 분포들에도 사용할 수 있어 국부적인 데이터 밀도 추정에 유용하다. 제안한 방법에서는 커널 밀도 추정을 수행한 후 밀도가 높은 지역에 클러스터의 초기 원형을 설정하고 원형이 설정된 영역의 밀도를 감소시키는 과정을 반복함으로써 효율적으로 초기 원형을 선택할 수 있다. 제안된 방법이 일반적으로 사용되는 무작위 초기화 방법에 비해 효율적이라는 사실은 실험 결과를 통해 확인할 수 있다.

Exploratory Methods for Joint Distribution Valued Data and Their Application

  • Igarashi, Kazuto;Minami, Hiroyuki;Mizuta, Masahiro
    • Communications for Statistical Applications and Methods
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    • 제22권3호
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    • pp.265-276
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    • 2015
  • In this paper, we propose hierarchical cluster analysis and multidimensional scaling for joint distribution valued data. Information technology is increasing the necessity of statistical methods for large and complex data. Symbolic Data Analysis (SDA) is an attractive framework for the data. In SDA, target objects are typically represented by aggregated data. Most methods on SDA deal with objects represented as intervals and histograms. However, those methods cannot consider information among variables including correlation. In addition, objects represented as a joint distribution can contain information among variables. Therefore, we focus on methods for joint distribution valued data. We expanded the two well-known exploratory methods using the dissimilarities adopted Hall Type relative projection index among joint distribution valued data. We show a simulation study and an actual example of proposed methods.

Estimation of P(X > Y) when X and Y are dependent random variables using different bivariate sampling schemes

  • Samawi, Hani M.;Helu, Amal;Rochani, Haresh D.;Yin, Jingjing;Linder, Daniel
    • Communications for Statistical Applications and Methods
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    • 제23권5호
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    • pp.385-397
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    • 2016
  • The stress-strength models have been intensively investigated in the literature in regards of estimating the reliability ${\theta}$ = P(X > Y) using parametric and nonparametric approaches under different sampling schemes when X and Y are independent random variables. In this paper, we consider the problem of estimating ${\theta}$ when (X, Y) are dependent random variables with a bivariate underlying distribution. The empirical and kernel estimates of ${\theta}$ = P(X > Y), based on bivariate ranked set sampling (BVRSS) are considered, when (X, Y) are paired dependent continuous random variables. The estimators obtained are compared to their counterpart, bivariate simple random sampling (BVSRS), via the bias and mean square error (MSE). We demonstrate that the suggested estimators based on BVRSS are more efficient than those based on BVSRS. A simulation study is conducted to gain insight into the performance of the proposed estimators. A real data example is provided to illustrate the process.