• Title/Summary/Keyword: 응용절사법

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사업체 양곡소비량 및 재고량조사 표본설계

  • Kim, Jin;Byeon, Ru-Na
    • Proceedings of the Korean Statistical Society Conference
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    • 2003.10a
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    • pp.59-62
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    • 2003
  • 양곡소비량조사는 가구부문과 사업체부문에서 소비하는 주요식품의 소비량을 조사함과 동시에 주곡인 쌀의 재고량을 조사한다. 이 조사는 해마다 통계청에서 표본설계하여 실시하는 표본조사에 의존한다. 특히, 사업체 부문의 양곡소비량 조사는 응용절사법(Modified Cut-Off Sampling Method)에 의해 표본추출되어 매년 11월에 조사가 실시되고 있다. 2003년도 사업체 양곡소비량 및 재고량조사는 2001년 사업체기초통계조사와 광공업통계조사를 모집단으로 하여 22,320 대상업체 중에서 819업체를 전수조사하고 2,145 업체를 표본조사하여 전체를 추계한다.

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Asymptotically Efficient L-Estimation for Regression Slope When Trimming is Given (절사가 주어질때 회귀기울기의 점근적 최량 L-추정법)

  • Sang Moon Han
    • The Korean Journal of Applied Statistics
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    • v.7 no.2
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    • pp.173-182
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    • 1994
  • By applying slope estimator under the arbitrary error distributions proposed by Han(1993), if we define regression quantiles to give upper and lower trimming part and blocks of data, we show the proposed slope estimator has asymptotically efficient slope estimator when the number of regression quantiles to from blocks of data goes to sufficiently large.

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A Study on Efficiency of the Cut-off Systematic Sampling (절사계통추출법의 효율성에 관한 연구)

  • 이계오;최정배;석영우
    • The Korean Journal of Applied Statistics
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    • v.14 no.1
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    • pp.111-120
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    • 2001
  • Either systematic sampling or stratified sampling is usually applied to the business conditions survey when companies don't have much difference in their size. But the cutoff systematic sampling is an efficient method when only a few companies are so large that the total of them almost equals to the total of whole companies. Throughout this paper, three estimators of total and their variance estimations depending on three kinds of sampling schemes are discussed, and are compared with them via their variances. It is proved that the cut-off systematic sampling is most efficient by using a real data of the logging business conditions survey.

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A Composite Estimator for the Take-Nothing Stratum of Cut-Off Sampling (복합추정량을 이용한 절사표본 총합 추정에 관한 연구)

  • Kim, Ji-Hak;Shin, Key-Il
    • The Korean Journal of Applied Statistics
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    • v.24 no.6
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    • pp.1115-1128
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    • 2011
  • Cut-off sampling that discards a part of the population from the sampling frame, is a widely used method for a highly skewed population like a business survey. Usually to the estimate of population total, we need to estimate the total of the take-nothing stratum. Many estimators have been developed to estimate the total of the take-nothing stratum. In this paper, we suggest a new composite estimator which combines the estimator suggested by Sarndal et al. (1992) and a ratio estimator obtained by small samples from the take-nothing stratum. Small simulation studies are performed for the comparison of the estimators and we confirm that the new suggested estimator is superior to the others.

A study for the efficiency of the cut-off method in highly skewed populations (왜도(Skewness)가 심한 모집단에서의 절사법효과에 관한 연구)

  • 한근식;김용철
    • The Korean Journal of Applied Statistics
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    • v.9 no.2
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    • pp.161-169
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    • 1996
  • In the design of the sampling, it is important to make a decision about the size of the sample to be selected from the population. We often have a problem to get the optical size of the sample to be considered for cost and time expended for selecting sample unit from highly skewed population. In this case, we give a graphical criterion with Take-all Stratum rate to choose a method and also illustrate the efficiency between the Neyman allocation and the cut-off method with real data.

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Sample Design for Materials and Components Industry Trend Survey (부품.소재산업 동향 조사의 표본설계)

  • NamKung, Pyong
    • Communications for Statistical Applications and Methods
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    • v.15 no.6
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    • pp.883-897
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    • 2008
  • This paper provides correct informations inflecting the present situation using the sample design in population that the National Statistical Office puts in operation of the mining and manufacturing industry statistical survey in 2006. This paper proposes new sampling design which is able to grasp business fluctuations and provide basic data for the rearing policy and management of the material industry and components industry. These sample design are the modified cut-off method and multivariate Neyman allocation using principal components and sampling method is the probability proportional systematic sampling.

A Study on the Optimal Cut-off Point in the Cut-off Sampling Method (절사표본에서 최적 절사점에 관한 연구)

  • Lee, Sang Eun;Cho, Min Ji;Shin, Key-Il
    • The Korean Journal of Applied Statistics
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    • v.27 no.3
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    • pp.501-512
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    • 2014
  • Modified cut-off sampling is widely used for highly skewed data. A serious drawback of modified cut-off sampling is the difficulty of adjustment of non-response in take-all stratum. Therefore, solutions of the problems of non-response in take-all stratum have been studied in various ways such as substitute of samples, imputation or re-weight method. In this paper, a new cut-off point based on minimizing MSE being used in exponential and power functions is suggested and it can be reduced the number of take-all stratum. We also investigate another cut-off point determination method with underlying distributions such as truncated log-normal and truncated gamma distributions. Finally we suggest the optimal cut-off point which has a minimum of take-all stratum size among suggested methods. Simulation studies are performed and Labor Survey data and simulated data are used for the case study.

Adaptive L-estimation for regression slope under asymmetric error distributions (비대칭 오차모형하에서의 회귀기울기에 대한 적합된 L-추정법)

  • 한상문
    • The Korean Journal of Applied Statistics
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    • v.6 no.1
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    • pp.79-93
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    • 1993
  • We consider adaptive L-estimation of estimating slope parameter in regression model. The proposed estimator is simple extension of trimmed least squares estimator proposed by ruppert and carroll. The efficiency of the proposed estimator is especially well compared with usual least squares estimator, least absolute value estimator, and M-estimators designed for asymmetric distributions under asymmetric error distributions.

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A Composite Estimator for Cut-off Sampling using Cost Function (절사표본 설계에서 비용함수를 고려한 복합추정량)

  • Sim, Hyo-Seon;Shin, Key-Il
    • The Korean Journal of Applied Statistics
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    • v.27 no.1
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    • pp.43-59
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    • 2014
  • Cut-off sampling has been widely used for a highly skewed population like a business survey by discarding a part of the population, so called a take-nothing stratum. For a more accurate estimate of the population total, Hwang and Shin (2013) suggested a composite estimator of a take-nothing stratum total that combined the survey results of a take-nothing stratum and a take-some sub-stratum (a part of take-some stratum). In this paper we propose a new cut-off sampling scheme by considering a cost function and a composite estimator based on the proposed sampling scheme. Small simulation studies compared the performances of known composite estimators and the new composite estimator suggested in this study. We also use Briquette Consumption Survey data for real data analysis.

L-Estimation for the Parameter of the AR(l) Model (AR(1) 모형의 모수에 대한 L-추정법)

  • Han Sang Moon;Jung Byoung Cheal
    • The Korean Journal of Applied Statistics
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    • v.18 no.1
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    • pp.43-56
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    • 2005
  • In this study, a robust estimation method for the first-order autocorrelation coefficient in the time series model following AR(l) process with additive outlier(AO) is investigated. We propose the L-type trimmed least squares estimation method using the preliminary estimator (PE) suggested by Rupport and Carroll (1980) in multiple regression model. In addition, using Mallows' weight function in order to down-weight the outlier of X-axis, the bounded-influence PE (BIPE) estimator is obtained and the mean squared error (MSE) performance of various estimators for autocorrelation coefficient are compared using Monte Carlo experiments. From the results of Monte-Carlo study, the efficiency of BIPE(LAD) estimator using the generalized-LAD to preliminary estimator performs well relative to other estimators.