• Title/Summary/Keyword: 비모수통계기법

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Reliability Analysis Using Parametric and Nonparametric Input Modeling Methods (모수적·비모수적 입력모델링 기법을 이용한 신뢰성 해석)

  • Kang, Young-Jin;Hong, Jimin;Lim, O-Kaung;Noh, Yoojeong
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.30 no.1
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    • pp.87-94
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    • 2017
  • Reliability analysis(RA) and Reliability-based design optimization(RBDO) require statistical modeling of input random variables, which is parametrically or nonparametrically determined based on experimental data. For the parametric method, goodness-of-fit (GOF) test and model selection method are widely used, and a sequential statistical modeling method combining the merits of the two methods has been recently proposed. Kernel density estimation(KDE) is often used as a nonparametric method, and it well describes a distribution function when the number of data is small or a density function has multimodal distribution. Although accurate statistical models are needed to obtain accurate RA and RBDO results, accurate statistical modeling is difficult when the number of data is small. In this study, the accuracy of two statistical modeling methods, SSM and KDE, were compared according to the number of data. Through numerical examples, the RA results using the input models modeled by two methods were compared, and appropriate modeling method was proposed according to the number of data.

A simulation study on projection pursuit discriminant analysis (투사지향방법에 의한 판별분석의 모의실험분석)

  • 안윤기;이성석
    • The Korean Journal of Applied Statistics
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    • v.5 no.1
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    • pp.103-111
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    • 1992
  • The projection pursuit method has been gussested as a technique for the analysis of the multivariate data. This method seeks out interesting linear projections of the multivariate data onto a line of a plane to solve the curse or dimensionality. In this paper we developed the discriminant analysis by using the projection method and simulations were used for comparison between this and other existing discriminant analysis methods.

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지하수 오염 분포도 작성에서 정규크리깅과 지시크리깅 기법의 상호 보완성 연구

  • 김태형;정상용;강동환;김민철;서상기
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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    • 2004.04a
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    • pp.477-481
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    • 2004
  • 지하수 수질자료의 분포가 광역적이고 자료의 수가 많은 지역과 자료의 분포가 국부적이고 갯수가 적은 지역을 선정하여, 모수적 통계기법인 정규크리깅과 비모수적 통계기법인 지시크리깅을 동시에 적용하였다. 베리오그램 분석은 각 수질자료의 원시 자료와 제한값을 적용하여 제한값 보다 낮거나 동일하면 '1' 의 값으로, 제한값 보다 높으면 '0' 의 값으로 변환된 자료에 대해 실시하였는데, 원시 염소이온 성분은 선형 모델이 선정되었으며, 비소 성분은 지수형 모델이 가장 적합한 것으로 선정되었다. 변환된 염소이온 성분과 비소 성분은 모두 구상형 모델이 가장 적합한 것으로 선정되었다. 정규크리깅과 지시크리깅 기법을 이용하여 지하수 오염 분포도를 작성하여 비교해 본 결과, 정규크리깅 기법은 연구지역의 자료 분포, 갯수와 범위의 영향을 크게 받는 것으로 나타났고, 지시크리깅 기법은 연구지역의 자료 분포와 특히 제한값에 따라 변환된 자료의 갯수의 영향을 크게 받는 것으로 나타났다. 정량적으로 나타낼 수 정규크리깅 기법과 정성적으로 나타낼 수 있는 지시크리깅 기법을 같이 적용한다면 지하수 오염 현황을 효과적으로 파악할 수 있을 것으로 판단된다.

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Model selection for unstable AR process via the adaptive LASSO (비정상 자기회귀모형에서의 벌점화 추정 기법에 대한 연구)

  • Na, Okyoung
    • The Korean Journal of Applied Statistics
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    • v.32 no.6
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    • pp.909-922
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    • 2019
  • In this paper, we study the adaptive least absolute shrinkage and selection operator (LASSO) for the unstable autoregressive (AR) model. To identify the existence of the unit root, we apply the adaptive LASSO to the augmented Dickey-Fuller regression model, not the original AR model. We illustrate our method with simulations and a real data analysis. Simulation results show that the adaptive LASSO obtained by minimizing the Bayesian information criterion selects the order of the autoregressive model as well as the degree of differencing with high accuracy.

비선형모형분석을 위한 탐색적 자료분석

  • Jang, Dae-Heung
    • Proceedings of the Korean Statistical Society Conference
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    • 2002.05a
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    • pp.25-28
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    • 2002
  • 비선형모형분석의 초기 단계에서 초기값(starting value, initial parameter value)를 결정하는 문제는 비선형모형의 모수추정을 위한 반복기법의 수렴속도나 국소값(local minimum)문제에 영향을 주게 된다. 본 논문을 통하여 탐색적 자료분석이 초기값를 결정하는 데 도움을 줄 수 있음을 보이고자 한다.

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Nonparametric method in one-way layout based on joint placement (일원배치법에서 결합위치를 이용한 비모수 검정법)

  • Jeon, Kyoung-Ah;Kim, Dongjae
    • The Korean Journal of Applied Statistics
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    • v.29 no.4
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    • pp.729-739
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    • 2016
  • Kruskal and Wallis (1952) proposed a nonparametric method to test the differences between more than three independent treatments. This procedure uses rank in mixed sample combined with more than three unlike populations. This paper proposes a the new procedure based on joint placements for a one-way layout as extension of the joint placements described in Chung and Kim (2007). A Monte Carlo simulation study is adapted to compare the power of the proposed method with previous methods.

A study comparison of mortality projection using parametric and non-parametric model (모수와 비모수 모형을 활용한 사망률 예측 비교 연구)

  • Kim, Soon-Young;Oh, Jinho
    • The Korean Journal of Applied Statistics
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    • v.30 no.5
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    • pp.701-717
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    • 2017
  • The interest of Korean society and government on future demographic structures is increasing due to rapid aging. Korea's mortality rate is decreasing, but the declined gap is variable. In this study, we compare the Lee-Carter, Lee-Miller, Booth-Maindonald-Smith model and functional data model (FDM) as well as Coherent FDM using non-parametric smoothing technique. We are then examine a reasonable model for projecting on mortality declined rate trend in terms of accuracy of mortality rate by ages and life expectancy. The possibility of using non-parametric techniques for the prediction of mortality in Korea was also examined. Based on the analysis results, FDM and Coherent FDM, which uses the non-parametric technique and reflects the trend of recent data, are excellent. As a result, FDM and Coherent FDM are good fit, and predictability is also excellent assuming no significant future changes.

Power study for 4 × 4 graeco-latin square design (4 × 4 그레코라틴방격모형의 검정력 연구)

  • Choi, Young-Hun
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.4
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    • pp.683-691
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    • 2012
  • In $4{\times}4$ graeco-latin square design, powers of rank transformed statistic for testing the main effect are superior to powers of parametric statistic without regard to the effect structure with equally or unequally spaced effect levels as well as the type of population distributions such as exponential, double exponential, normal and uniform distribution. As numbers of block effect or effect sizes are decreased, powers of rank transformed statistic are much higher than powers of parametric statistic. In case that block effects are smaller than a main effect or one block effect is higher than other block effects, powers of rank transformed statistic are much higher than powers of parametric statistic in $4{\times}4$ graeco-latin square design with three block effects and one main effect.

완전확률화모형 및 랜덤화블럭모형하에서 순위변환을 이용한 다중비교의 시뮬레이션 분석

  • 최영훈
    • Communications for Statistical Applications and Methods
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    • v.5 no.1
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    • pp.85-97
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    • 1998
  • 완전확률화모형 및 랜덤화블럭모형하에서의 주요한 다중비교 분석기법들을 시뮬레이션을 이용하여 검토하고자 하였다. 시뮬레이션 결과는 순위변환과 최소유의차검정을 이용한 다중비교 분석기법이 모수적 ANOVA F 검정과 Fisher의 유의차검정, 비모수적 Kruskal-Wallis 검정과 최소유의차검정 및 Friedman 검정과 최소유의차검정을 이용한 분석기법보다 전체실험오차율, 전체실험검정력 및 개별쌍검정력 면에서 상대적으로 뛰어남을 보여준다. 즉 순위변환한 ANOVA F 검정의 전체실험오차율은 명목상의 유의수준을 잘 유지하고 있으며, 전체실험검정력 및 개별쌍검정력은 모수적 ANOVA F 검정과 Kruskal-Wallis 검정 및 Friedman 검정기법보다 전반적으로 우수함을 알 수 있다.

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Confidence Intervals for High Quantiles of Heavy-Tailed Distributions (꼬리가 두꺼운 분포의 고분위수에 대한 신뢰구간)

  • Kim, Ji-Hyun
    • The Korean Journal of Applied Statistics
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    • v.27 no.3
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    • pp.461-473
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    • 2014
  • We consider condence intervals for high quantiles of heavy-tailed distribution. The asymptotic condence intervals based on the limiting distribution of estimators are considered together with bootstrap condence intervals. We can also apply a non-parametric, parametric and semi-parametric approach to each of these two kinds of condence intervals. We considered 11 condence intervals and compared their performance in actual coverage probability and the length of condence intervals. Simulation study shows that two condence intervals (the semi-parametric asymptotic condence interval and the semi-parametric bootstrap condence interval using pivotal quantity) are relatively more stable under the criterion of actual coverage probability.