• Journal of the Korean Data and Information Science Society
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• 제24권4호
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• pp.815-824
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• 2013

국가단위의 조사와 같은 대규모 표본조사에서는 표본의 대표성을 확보하기 위해 층화, 집락, 계통, 불균등확률추출 등을 종합적으로 사용하는 복합표본설계가 일반화되어 있다. 이러한 복합표본설계에 기초한 범주형 자료분석에서는 자료의 독립성과 다항분포를 가정하는 전통적인 피어슨검정이 왜곡된 검정결과를 가져올 수 있다. 본 연구는 복합표본설계에 의한 범주형조사자료의 k-모집단 동질성검정에서 설계기반 일치통계량인 Wald 검정통계량을 유도하고, 전통적인 피어슨검정통계량을 사용할 경우 발생할 수 있는 오차요인을 항목별로 분해하여, 분산의 편의에 의한 영향, 추정량의 편의에 의한 영향, 기타 분산의 편의와 추정량의 편의가 교락되어 미치는 영향으로 각각 분해하는 식을 도출하였다. 또한, 도출된 식의 각 항목이 피어슨 카이제곱검정통계량에 미치는 상대적 크기를 경험적으로 확인하기 위해 국민건강영양조사 제4기 2차년도 자료를 이용해 경험분석 하였다. 분석결과, 변수에 따른 차이는 있지만 대체로 분산의 편의가 미치는 영향이 추정량의 편의가 미치는 영향보다 크다는 것을 명확히 확인할 수 있었다.

• Communications for Statistical Applications and Methods
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• 제30권4호
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• pp.403-410
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• 2023

Two-Phase sampling, which was first introduced by Neyman (1938), has various applications in different forms. Variance estimation for two-phase sampling has been an important research topic because conventional variance estimators used in most softwares are not working. In this paper, we considered a variance estimation for two-phase sampling in which stratified two-stage cluster sampling designs are used in both phases. By defining a conditionally unbiased estimator of an approximate variance estimator, which is calculable when all elements in the first phase sample are observed, we propose an explicit form of variance estimator of the double expanded estimator for a two-phase sample. A small simulation study shows the proposed variance estimator has a negligible bias with small variance. The suggested variance estimator is also applicable to other linear estimators of the population total or mean if appropriate residuals are defined.

• Journal of applied mathematics & informatics
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• 제8권3호
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• pp.975-987
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• 2001

We treat the problem of variance estimation for the estimator of population total, which is derived from the calibration estimation procedure corresponding to the levels of auxiliary information under nonresponse situation. We develop the calibrated variance estimation procedure using the fact that the population total and variance as well as the sample total and variance of the auxiliary variable are known. We show that the proposed variance estimation procedure improves the $Lundst\ddot{o}rm$ and $S\ddot{a}rndal's$ (1999) procedure with respect to the variance and nonresponse bias reduction through the simulation study.

• 응용통계연구
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• 제25권1호
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• pp.15-27
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• 2012

본 논문에서는 KOSPI 시가총액기준 상위 4종목(삼성전자, 현대차, 현대모비스, POSCO)의 고빈도 거래 데이터를 바탕으로 일중 수익률의 실현변동성과 시장미시구조잡음에 대해 연구한다. Volatility signature plot을 통해 실현변동성(Realized Variance; RV)과 편의수정 실현변동성($RV_{AC_1}$)의 편의를 확인하고 시장미시구조 잡음의 특징을 실증적으로 파악한다. 또한, 잡음 대 신호비(Noise-to-Signal Ratio; NSR)를 사용하여, 평균제곱오차(Mean Square Error; MSE) 기준의 실현변동성(RV)과 편의수정 실현변동성($RV_{AC_1}$)의 최적 추출 빈도수를 추정해본다.

• Communications for Statistical Applications and Methods
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• 제9권1호
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• pp.249-259
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• 2002

In order to estimate the mean and variance for a Normal distribution which is truncated at both right and left sides, maximum likelihood estimators based on the entire sample from the original distribution are compared with the sample mean and variance of the censored sample which is the data remaining after truncation using simulation. We found that, surprisingly, the mean squared error of the mean based on the censored data Is smaller than that of the full sample estimators.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.38-45
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• 2011

Studies have shown that infrastructure projects have continued to experience significant delays and cost overrun over an extended period of time and no evidence of learning ever have happened [1] [2]. Various causes contribute to the bias towards overrun [3]. This study contributes to literature by developing and subsequently validating a set of hypothesized relationships between project complexity and project performance. The results show that project complexity is associated with both the magnitude and variance of overrun. Further, the extent and magnitude of the positive bias towards overrun are moderated by project complexity.

• Asian-Australasian Journal of Animal Sciences
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• 제10권5호
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• pp.510-513
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• 1997

This study examined the effects of ignoring inbreeding depression on (co)variance components for weaning weight through the use of Monte Carlo simulation. Weaning weight is of particular interest as a trait for which additive direct and maternal genetic components exist and there then is the potential for a direct-maternal genetic covariance. Ignoring inbreeding depression in the analytical model (.8 kg reduction of phenotypic value per 1% inbreeding) led to biased estimates of all genetic (co) variance components, all estimates being larger than the true values of the parameters. In particular, a negative bias in the direct-maternal genetic covariance was observed in analyses that ignored inbreeding depression. A small spurious sire-by-year interaction variance was also observed.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 추계 학술발표회 논문집
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• pp.123-130
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• 2003

We define a broad class of rotation designs whose monthly sample is balanced in interview time, level of recall, and rotation group, and whose rotation scheme is time-invariant. The necessary and sufficient conditions are obtained for such designs. Using these conditions, we derive a minimum variance unbiased generalized composite estimator (MVUGCE). To examine the existence of time-in-sample bias and recall bias, we also propose unbiased estimators and their variances. Numerical examples investigate the impacts of design gap, non-sampling error sources, and two types of correlations on the variance of MVUGCE.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.279-282
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• 1997

Bayesian reconstruction methods for emission computed tomography have been a topic of interest in recent years, partly because they allow for the introduction of prior information into the reconstruction problem. Early formulations incorporated priors that imposed simple spatial smoothness constraints on the underlying object using Gibbs priors in the form of four-nearest or eight-nearest neighbors. While these types of priors, known as "membrane" priors, are useful as stabilizers in otherwise unstable ML-EM reconstructions, more sophisticated prior models are needed to model underlying source distributions more accurately. In this work, we investigate whether the "thin plate" model has advantages over the simple Gibbs smoothing priors mentioned above. To test and compare quantitative performance of the reconstruction algorithms, we use Monte Carlo noise trials and calculate bias and variance images of reconstruction estimates. The conclusion is that the thin plate prior outperforms the membrane prior in terms of bias and variance.

• 대한수학회보
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• 제48권3호
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• pp.523-537
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• 2011

A receiver operating characteristic (ROC) curve plots the true positive rate of a classier against its false positive rate, both of which are accuracy measures of the classier. The ROC curve has several interesting geometrical properties, including concavity which is a necessary condition for a classier to be optimal. In this paper, we study the nonparametric maximum likelihood estimator (NPMLE) of a concave ROC curve and its modification to reduce bias. We characterize the NPMLE as a solution to a geometric programming, a special type of a mathematical optimization problem. We find that the NPMLE is close to the convex hull of the empirical ROC curve and, thus, has smaller variance but positive bias at a given false positive rate. To reduce the bias, we propose a modification of the NPMLE which minimizes the $L_1$ distance from the empirical ROC curve. We numerically compare the finite sample performance of three estimators, the empirical ROC curve, the NMPLE, and the modified NPMLE. Finally, we apply the estimators to estimating the optimal ROC curve of the variance-threshold classier to segment a low depth of field image and to finding a diagnostic tool with multiple tests for detection of hemophilia A carrier.