• Title/Summary/Keyword: 비모수적 추정

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오차분산의 추정에 대한 고찰

  • 김종태;고정환
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 1999.05a
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    • pp.185-190
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    • 1999
  • 비모수 회귀모형에 있어서의 오차분산을 추정하는 방법들 중 차분에 기저한 방법(difference-based methods)을 이용한 기존의 추정량들을 비교 분석하는데 목적이 있다. 특히 점근적인 최적 이차차분에 기저한 Hall과 Kay, Titterington(1990)의 HKT 추정량에 대한 그들의 추정량에 대한 문제점들을 제시하고, HKT추정량과, GSJS 추정량, Rice 추정량에 대하여 모의실험을 이용하여 모수에 대한 수렴속도를 비교 분석하였다. 또한 GSJS 추정량에 대한 일치성과 수렴 속도를 보였다.

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붓스트랩 표준편차 추정량으로 표준화한 U-통계량을 이용한 비모수적 검정법

  • 이기훈
    • Communications for Statistical Applications and Methods
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    • v.2 no.2
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    • pp.221-226
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    • 1995
  • 본 연구는 붓스트랩에 의한 U-통계량의 분산추정방법을 제안하고, 추정량의 일치성을 증명하였다. 결과적으로 붓스트랩 추정량으로 표준화한 U-통계량의 값이 표준정규분포에 근사함을 보였다. 또한 실제적인 비모수검정에서 이를 응용하여 검정력과 특성을 연구하였다.

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Comparison of Two Parametric Estimators for the Entropy of the Lognormal Distribution (로그정규분포의 엔트로피에 대한 두 모수적 추정량의 비교)

  • Choi, Byung-Jin
    • Communications for Statistical Applications and Methods
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    • v.18 no.5
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    • pp.625-636
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    • 2011
  • This paper proposes two parametric entropy estimators, the minimum variance unbiased estimator and the maximum likelihood estimator, for the lognormal distribution for a comparison of the properties of the two estimators. The variances of both estimators are derived. The influence of the bias of the maximum likelihood estimator on estimation is analytically revealed. The distributions of the proposed estimators obtained by the delta approximation method are also presented. Performance comparisons are made with the two estimators. The following observations are made from the results. The MSE efficacy of the minimum variance unbiased estimator appears consistently high and increases rapidly as the sample size and variance, n and ${\sigma}^2$, become simultaneously small. To conclude, the minimum variance unbiased estimator outperforms the maximum likelihood estimator.

On Practical Choice of Smoothing Parameter in Nonparametric Classification (베이즈 리스크를 이용한 커널형 분류에서 평활모수의 선택)

  • Kim, Rae-Sang;Kang, Kee-Hoon
    • Communications for Statistical Applications and Methods
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    • v.15 no.2
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    • pp.283-292
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    • 2008
  • Smoothing parameter or bandwidth plays a key role in nonparametric classification based on kernel density estimation. We consider choosing smoothing parameter in nonparametric classification, which optimize the Bayes risk. Hall and Kang (2005) clarified the theoretical properties of smoothing parameter in terms of minimizing Bayes risk and derived the optimal order of it. Bootstrap method was used in their exploring numerical properties. We compare cross-validation and bootstrap method numerically in terms of optimal order of bandwidth. Effects on misclassification rate are also examined. We confirm that bootstrap method is superior to cross-validation in both cases.

Comparing the efficiency of dispersion parameter estimators in gamma generalized linear models (감마 일반화 선형 모형에서의 산포 모수 추정량에 대한 효율성 연구)

  • Jo, Seongil;Lee, Woojoo
    • The Korean Journal of Applied Statistics
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    • v.30 no.1
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    • pp.95-102
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    • 2017
  • Gamma generalized linear models have received less attention than Poisson and binomial generalized linear models. Therefore, many old-established statistical techniques are still used in gamma generalized linear models. In particular, existing literature and textbooks still use approximate estimates for the dispersion parameter. In this paper we study the efficiency of various dispersion parameter estimators in gamma generalized linear models and perform numerical simulations. Numerical studies show that the maximum likelihood estimator and Cox-Reid adjusted maximum likelihood estimator are recommended and that approximate estimates should be avoided in practice.

VAR를 이용한 금융위험 측정

  • Yu, Il-Seong;Lee, Yu-Tae
    • The Korean Journal of Financial Studies
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    • v.10 no.1
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    • pp.191-214
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    • 2004
  • VaR에 의한 금융위험의 측정은 국제결제은행 바젤위원회의 내부모델 허용에 힘입어 금융산업에서 표준방식으로 확고한 입지를 차지하고 있다. 본 연구에서는 한국주식시장포트폴리오를 거래투자자산으로 보유한 경우의 VaR를 극단치이론에 입각하여 측정하고 이의 성과를 RiskMetrics의 성과와 비교하여 검토하였다. GPD의 모수적 추정에 의한 VaR의 사후검정결과는 표본내 사후검정이나 표본외 사후검정에서 어떤 신뢰수준에서도 기대되는 범위와 크게 벗어나지 않은 안정된 결과를 보였다. RiskMetrics의 EWMA방식도 역시 표본내와 표본외 사후검정 어느 경우에나 기대되는 범위에서 크게 벗어나지 않았지만 높은 신뢰수준에서는 그 성과가 GPD VaR에 비하여 상대적으로 불안정하였으며 위험의 과소평가 성향을 확인할 수 있었다. 비모수적 GEV추정에 입각한 VaR의 경우에는 위험을 과대평가하고 지나치게 보수적인 성향을 나타내었다. GPD의 모수적 접근에 의한 VaR 측정은 다양한 신뢰수준에서 정확한 검정결과를 보여주고 있으며, 시간적 흐름에 따르는 VaR의 행태도 지나친 변동성을 보이지 않아 외부규제 및 내부통제를 위한 금융위험의 측정지표로서 실용적인 가치가 있음을 확인할 수 있다.

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Testing the Existence of a Discontinuity Point in the Variance Function

  • Huh, Jib
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.3
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    • pp.707-716
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    • 2006
  • When the regression function is discontinuous at a point, the variance function is usually discontinuous at the point. In this case, we had better propose a test for the existence of a discontinuity point with the regression function rather than the variance function. In this paper we consider that the variance function only has a discontinuity point. We propose a nonparametric test for the existence of a discontinuity point with the second moment function since the variance function and the second moment function have the same location and jump size of the discontinuity point. The proposed method is based on the asymptotic distribution of the estimated jump size.

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A study on a nonparametric test for ordered alternatives in regreesion problem (회귀직선에서 순서대립가설에 대한 비모수적 검정법 연구)

  • 이기훈
    • The Korean Journal of Applied Statistics
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    • v.6 no.2
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    • pp.237-245
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    • 1993
  • A nonparametric test for the parallelisim of k regression lines against ordered alternatives is proposed. The test statistic is weighted Jonckheere-type statistic applied to slope estimators obtained from each lines. The distribution of the proposed test statistic is asymptotically distribution-free. From the viewpoint of efficiencies, the proposed test desirable properties and is more efficient than the other nonparametric tests.

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A comparison and prediction of total fertility rate using parametric, non-parametric, and Bayesian model (모수, 비모수, 베이지안 출산율 모형을 활용한 합계출산율 예측과 비교)

  • Oh, Jinho
    • The Korean Journal of Applied Statistics
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    • v.31 no.6
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    • pp.677-692
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    • 2018
  • The total fertility rate of Korea was 1.05 in 2017, showing a return to the 1.08 level in the year 2005. 1.05 is a very low fertility level that is far from replacement level fertility or safety zone 1.5. The number may indicate a low fertility trap. It is therefore important to predict fertility than at any other time. In the meantime, we have predicted the age-specific fertility rate and total fertility rate by various statistical methods. When the data trend is disconnected or fluctuating, it applied a nonparametric method applying the smoothness and weight. In addition, the Bayesian method of using the pre-distribution of fertility rates in advanced countries with reference to the three-stage transition phenomenon have been applied. This paper examines which method is reasonable in terms of precision and feasibility by applying estimation, forecasting, and comparing the results of the recent variability of the Korean fertility rate with parametric, non-parametric and Bayesian methods. The results of the analysis showed that the total fertility rate was in the order of KOSTAT's total fertility rate, Bayesian, parametric and non-parametric method outcomes. Given the level of TFR 1.05 in 2017, the predicted total fertility rate derived from the parametric and nonparametric models is most reasonable. In addition, if a fertility rate data is highly complete and a quality is good, the parametric model approach is superior to other methods in terms of parameter estimation, calculation efficiency and goodness-of-fit.

Prediction Intervals for Nonlinear Time Series Models Using the Bootstrap Method (붓스트랩을 이용한 비선형 시계열 모형의 예측구간)

  • 이성덕;김주성
    • The Korean Journal of Applied Statistics
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    • v.17 no.2
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    • pp.219-228
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    • 2004
  • In this paper we construct prediction intervals for nonlinear time series models using the bootstrap. We compare these prediction intervals to traditional asymptotic prediction intervals using quasi-score estimation function and M-quasi-score estimating function comprising bounded functions. Simulation results show that the bootstrap method leads to improved accuracy. The accuracy of the bootstrap is empirically demonstrated with the consumer price index.