• 응용통계연구
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• 제21권1호
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• pp.177-182
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• 2008

공통분산을 갖는 두 모집단에서 얻은 두 독립표본 자료로부터 공통분산을 추정하거나, 한 모집단에서 얻는 두 자료의 혼합자료로부터 모분산을 추정할때 각 표본분산의 가중평균값인 합동추정량(pooled estimator)을 주로 사용한다. 본 논문에서는 동일한 모집단에서 얻은 혼합자료의 표본분산 식을 각 자료의 평균과 분산만 이용하여 구한 후 합동추정량과 비교한다.

• 품질경영학회지
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• 제22권4호
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• pp.59-78
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• 1994

In some observational studies, we have often random censoring model. However, the data available may be partially observable censored data consisting of the observed failure times and only those nonfailure times which are subject to follow up. In this paper, we present an extension of the problem of partially parametric estimation of the survival function to such partially observable censored data. The proposed estimator treats the observed failure times nonparametrically and uses a parametric model only for those nonfailure times which are subject to follow-up. We discuss the motivation and construction of the proposed estimator and investigate the limiting properties of the proposed estimator such as asymptotic normality. Also, when the assumed parametric model is exponential, the asymptotic variance of the estimator is obtained. Furthermore, an example is given to compare the proposed estimator with the modified Kaplan Meier(MKM) estimator. From the results, it is shown that the relative efficiency of the proposed estimator is higher than that of the MKM estimator in the follow-up study with increasing time.

• Communications for Statistical Applications and Methods
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• 제19권2호
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• pp.287-292
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• 2012

Sample periodogram is widely known as an inconsistent estimator for true spectral density. We show that it becomes consistent when the true spectrum at the zero frequency (often known as long-run variance) equals zero. Asymptotic results for consistency of the periodogram as well as the rate of convergence are formally derived.

• Journal of the Korean Statistical Society
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• 제35권1호
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• pp.1-23
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• 2006

In this paper we consider an estimation of the discontinuous variance function in nonparametric heteroscedastic random design regression model. We first propose estimators of the change point in the variance function and then construct an estimator of the entire variance function. We examine the rates of convergence of these estimators and give results for their asymptotics. Numerical work reveals that using the proposed change point analysis in the variance function estimation is quite effective.

• Journal of the Korean Data and Information Science Society
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• 제5권2호
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• pp.19-27
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• 1994

It is known that the maximum likelihood method does not provide explicit estimator for the scale parameter of the Weibull distribution based on Type-II censored samples. In this paper we provide an approximate maximum likelihood estimator (AMLE) of the scale parameter of the Weibull distribution with Type-II censoring. We obtain the asymptotic variance and simulate the values of the bias and the variance of this estimator based on 3000 Monte Carlo runs for n = 10(10)30 and r,s = 0(1)4. We also simulate the absolute biases of the MLE and the proposed AMLE for complete samples. It is found that the absolute bias of the AMLE is smaller than the absolute bias of the MLE.

• 품질경영학회지
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• 제10권1호
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• pp.2-6
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• 1982

m개의 부품으로 이루어진 씨스템이 스트레스를 받고 있다고 가정하자. 본 논문에서는 스트레스 분포와 스트렝스 분포로 부터의 확률표본으로 자료가 구성되어 있을때, 이 씨스템의 신뢰도에 대하여 고찰하였다. 모든 분포는 미지의 모수를 가진 독립적인 지수 분포인 것으로 가정하였다. 씨스템 신뢰도의 형태와 최소분산 불편추정량을 구하였다. 또한, 최소분산 불편추정량을 최우추정량에 대하여 전개하고 두 추정량의 등가성을 보임으로서 근사분포를 구하였다. 몬테카를로 씨뮤레이션으로 두 추정량의 효율을 비교하였다.

• Journal of the Korean Data and Information Science Society
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• 제20권3호
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• pp.577-585
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• 2009

So far in a nonparametric regression model one of the interesting problems is estimating the error variance. In this paper we propose an estimator of the mean of the squared functions which is the numerator of SNR (Signal to Noise Ratio). To estimate SNR, the mean of the squared function should be firstly estimated. Our focus is on estimating the amplitude, that is the mean of the squared functions, in a nonparametric regression using a simple linear regression model with the quadratic form of observations as the dependent variable and the function of a lag as the regressor. Our method can be extended to nonparametric regression models with multivariate functions on unequally spaced design points or clustered designed points.

• International Journal of Aeronautical and Space Sciences
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• 제2권2호
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• pp.73-81
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• 2001

This paper describes the procedure to develop a robust estimator design method for a target tracker that accounts for both structured real parameter uncertainties and unknown inputs. Two robust design approaches are combined: the Mini-p-Norm. design method to consider real parameter uncertainties and the $H_{\infty}$ design technique for unknown disturbances and unknown inputs. Constant estimator gains are computed that guarantee the robust performance of the estimator in the presence of parameter variations in the target model and unknown inputs to the target. The new estimator has two design parameters. One design parameter allows the trade off between small estimator error variance and low sensitivity to unknown parameter variations. Another design parameter allows the trade off between the robustness to real parameter variations and the robustness to unknown inputs. This robust estimator design method was applied to the longitudinal motion tracking problem of a T-38 aircraft.

• 응용통계연구
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• 제20권1호
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• pp.79-89
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• 2007

Arizono와 Ohta(1989)에 의해 소개된 정규성 검정은 쿨백-라이블러 판별정보를 이용하고 있으며, 검정통계량의 유도에 기반이 되는 판별정보의 추정량을 얻기 위해 Vasicek(1976)의 표본엔트로피와 분산의 최대가능도 추정량을 사용했다. 그런데 두 추정량은 편향성을 가지게 되므로 보다 정확한 판별정보의 추정을 위해 비편향 추정량을 사용하는 것이 바람직하다. 본 논문에서는 편향을 수정한 엔트로피 추정량과 분산의 균일최소분산비편향 추정량을 사용하여 판별정보의 추정량을 구하고 이로부터 유도되는 검정통계량을 사용하는 개선된 정규성 검정을 제시한다. 제안한 검정의 특성을 규명하고 검정력 비교를 위해서 모의실험을 수행한다.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2002년도 추계 학술발표회 논문집
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• pp.103-108
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• 2002

We consider an estimation of discontinuous variance function in nonparametric heteroscedastic random design regression model. We first propose estimators of a change point and jump size in variance function and then construct an estimator of entire variance function. We examine the rates of convergence of these estimators and give results on their asymptotics. Numerical work reveals that the effectiveness of change point analysis in variance function estimation is quite significant.