• 한국조사연구학회:학술대회논문집
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• 한국조사연구학회 2001년도 추계학술대회 발표논문집
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• pp.77-85
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• 2001

무응답 상황하에서 보정 추정량에 대해 관심변수와 강한 상관계수를 가진 보조정보의 수준에 따라 모집단 총합에 대한 추정량과 분산추정량을 붓스트랩 방법을 이용해서 구했다. 이때 존재하는 보조정보의 수준이 표본인 경우와 모집단인 경우로 나누어 모집단 총합에 대한 보정 추정량(calibration estimator)을 구하고, 그에 따른 붓스트랩 분산 추정량을 도출하였다. 또한 테일러 분산 추정량, 잭나이프 분산 추정량과 붓스트램 분산 추정량의 효율성을 모의 실험을 통해 비교해 보았다.

• Journal of the Korean Data and Information Science Society
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• 제20권2호
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• pp.349-356
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• 2009

국내의 행정구역상 시군구 등과 같은 소지역에 있어서 실업률에 대한 남녀별 공통 상대위험도를 추정하는데, 추정방법으로 단순한 합동추정, 울프 방법에 기초한 가중추정과 잭나이프 추정들을 고려하고 이 추정 방법들의 효율성을 편의와 평균제곱오차의 개념을 통해서 비교하고자 한다. 이를 위해 2002년 12월 경기지역의 경제활동인구조사 자료를 이용하여 이 지역 내의 24개 시군단위 소지역들의 남녀별 실업률에 대한 상대위험도의 편의 및 평균제곱오차가 본 연구에서 제시된 추정절차에 의해 추정된다. 또한, 이들 추정치들의 안정성과 신뢰성은 상대편의와 상대오차제곱근을 통하여 비교된다. 추정결과 잭나이프 추정이 다른 두 추정들에 비해 매우 효율적임을 보였다.

• Communications for Statistical Applications and Methods
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• 제3권3호
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• pp.291-297
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• 1996

In this paper, we propose the jackknife estimator and the bootstrap estimator of Gini index of the two-parameter exponential distribution when the location parameter $\theta$ is unknown and the scale parameter $\sigma$is known. Sinilarly, we propose the bias location parameter $\theta$ and the scale parameter $\sigma$ are unknown. The bootstrap estimator is more efficient than the other estimators when the location parameter $\theta$is unknown and the scale parameter $\sigma$ is known, and the bias corrected estimator is more efficient than the MLE when both the location parameter $\theta$ and the scale parameter $\sigma$are unknown.

• Communications for Statistical Applications and Methods
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• 제11권3호
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• pp.583-595
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• 2004

For the Korean Economically Active Population Survey(EAPS), we consider the composite estimator based on logistic regression model to estimate the unemployment rate for small areas(Si/Gun). Also, small area estimation technique based on hierarchical generalized linear model is proposed to include the random effect which reflect the characteristic of the small areas. The proposed estimation techniques are applied to real domestic data which is from the Korean EAPS of Choongbuk. The MSE of these estimators are estimated by Jackknife method, and the efficiencies of small area estimators are evaluated by the RRMSE. As a result, the composite estimator based on logistic model is much more efficient than others and it turns out that the composite estimator can produce the reliable estimates under the current EAPS system.

• The Journal of Asian Finance, Economics and Business
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• 제5권1호
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• pp.11-16
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• 2018

This research examines the alternative ways of estimating the coefficient of non-diversifiable risk, namely beta coefficient, in Capital Asset Pricing Model (CAPM) introduced by Sharpe (1964) that is an essential element of assessing the value of diverse assets. The non-parametric methods used in this research are the robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator). The Jackknife, the resampling technique, is also employed to validate the results. According to finance literature and common practices, these coecients have often been estimated using Ordinary Least Square (LS) regression method and monthly return data set. The empirical results of this research pointed out that the robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator) performed much better than Ordinary Least Square (LS) in terms of eciency for large-cap stocks trading actively in the United States markets. Interestingly, the empirical results also showed that daily return data would give more accurate estimation than monthly return data in both Ordinary Least Square (LS) and robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator) regressions.

• 한국국방경영분석학회지
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• 제6권2호
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• pp.129-149
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• 1980

In medical follow-up, equipment lifetesting, various military situations, and other fields, one often desires to calculate survival probability as a function of time, p(t). If the observer is able to record the time of occurrence of the event of interest (called a 'death'), then an empirical, non-parametric estimate may simply by obtained from the fraction of survivors after various elapsed times. The estimation is more complicated when the data are truncated, i.e., when the observer loses track of some individuals before death occurs. The product-limit method of Kaplan and Meier is one way of estimating p(t) when the mechanism causing truncation is independent of the mechanism causing death. This paper proposes jackknife estimators of logistic trans-formation and compares it to the product-limit method. A computer simulation is used to generate the times of death and truncation from a variety of assumed distributions.

• Journal of the Korean Data and Information Science Society
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• 제28권2호
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• pp.443-449
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• 2017

Estimation of population proportion like the distribution rate of LED TV and the prevalence of a disease are often estimated based on survey sample data. Population proportion is generally considered as a special form of population mean. In complex sampling like stratified multistage sampling with unequal probability sampling, the denominator of mean may be random variable and it is estimated like ratio estimator. In this research, we examined the estimation of distribution rate based on stratified multistage sampling, and determined some numerical outcomes using stratified random sample data with about 25% of missing observations. In the data used for this research, the survey weight was determined by deterministic way. So, the weights are not random variable, and the population distribution rate and its variance estimator can be estimated like population mean estimation. When the weights are not random variable, if one estimates the variance of proportion estimator using ratio method, then the variances may be inflated. Therefore, in estimating variance for population proportion, we need to examine the structure of data and survey design before making any decision for estimation methods.

• Communications for Statistical Applications and Methods
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• 제22권5호
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• pp.435-443
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• 2015

Two phase sampling design is useful to increase estimation efficiency using deep stratification, improved non-response adjustment and reduced coverage bias. The same sampling units are commonly used for the first and the second phases in complex two-phase sampling design. In this paper we consider a sampling scheme where the first phase sampling units are clusters and the second phase sampling units are list samples. Using selected clusters in first phase requires that we list up elements in the selected clusters from the first phase and then use the list as a secondary sampling frame for the second phase sampling design. Then we select second phase samples from the listed sampling frame. We suggest an estimator based on the complex two-phase sampling design with different sampling units of each phase. Also the estimated variances of the estimator obtained by using classic and replication variance methods are considered and compared using simulation studies. For real data analysis, 2010 Korea Farm Household Economy Survey (KFHES) and 2011 Korea Agriculture Survey (KAS) are used.

• Communications for Statistical Applications and Methods
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• 제24권4호
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• pp.339-351
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• 2017

Resampling approaches were the first techniques employed to compute a variance for the Gini coefficient; however, many authors have shown that an analysis of the Gini coefficient and its corresponding variance can be obtained from a regression model. Despite the simplicity of the regression approach method to compute a standard error for the Gini coefficient, the use of the proposed regression model has been challenging in economics. Therefore in this paper, we focus on a comparative study among the regression approach and resampling techniques. The regression method is shown to overestimate the standard error of the Gini index. The simulations show that the Gini estimator based on the modified regression model is also consistent and asymptotically normal with less divergence from normal distribution than other resampling techniques.

• Communications for Statistical Applications and Methods
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• 제18권2호
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• pp.155-164
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• 2011

This paper suggests two ratio-cum-product estimators of finite population mean using known coefficient of variation and co-efficient of kurtosis of auxiliary characters. The bias and mean squared error of the proposed estimators with large sample approximation are derived. It has been shown that the estimators suggested by Upadhyaya and Singh (1999) are particular case of the suggested estimators. Almost ratio-cum product estimators of suggested estimators have also been obtained using Jackknife technique given by Quenouille (1956). An empirical study is also carried out to demonstrate the performance of the suggested estimators.