• Title/Summary/Keyword: Sampling error

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Design and Estimation of Multiple Acceptance Sampling Plans for Stochastically Dependent Nonstationary Processes (확률적으로 종속적인 비평형 다단계 샘플링검사법의 설계 및 평가)

  • Kim, Won-Kyung
    • Journal of Korean Institute of Industrial Engineers
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    • v.25 no.1
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    • pp.8-20
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    • 1999
  • In this paper, a design and estimation procedure for the stochastically dependent nonstationary multiple acceptance sampling plans is developed. At first, the rough-cut acceptance and rejection numbers are given as an initial solution from the corresponding sequential sampling plan. A Monte-Carlo algorithm is used to find the acceptance and rejection probabilities of a lot. The conditional probability formula for a sample path is found. The acceptance and rejection probabilities are found when a decision boundary is given. Several decision criteria and the design procedure to select optimal plans are suggested. The formula for measuring performance of these sampling plans is developed. Type I and II error probabilities are also estimated. As a special case, by setting the stage size as 1 in a dependent sampling plan, a sequential sampling plan satisfying type I and II error probabilities is more accurate and a smaller average sample number can be found. In a numerical example, a Polya dependent process is examined. The sampling performances are shown to compare the selection scheme and the effect of the change of the dependency factor.

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Linear Measurement Error Variance Estimation based on the Complex Sample Survey Data

  • Heo, Sunyeong;Chang, Duk-Joon
    • Journal of Integrative Natural Science
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    • v.5 no.3
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    • pp.157-162
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    • 2012
  • Measurement error is one of main source of error in survey. It is generally defined as the difference between an observed value and an underlying true value. An observed value with error may be expressed as a function of the true value plus error term. In some cases, the measurement error variance may be also a function of the unknown true value. The error variance function can be rewritten as a function of true value multiplied by a scale factor. This research explore methods for estimation of the measurement error variance based on the data from complex sampling design. We consider the case in which the variance of mesurement error is a linear function of unknown true value, and the error variance scale factor is small. We applied our results to the U.S. Third National Health and Nutrition Examination Survey (the U.S. NHANES III) data for empirical analyses, which has replicate measurements for relatively small subset of initial respondents's group.

Probability Sampling to Select Polling Places in Exit Poll (출구조사를 위한 투표소 확률추출 방법)

  • Kim, Young-Won;Uhm, Yoon-Hee
    • Survey Research
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    • v.6 no.2
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    • pp.1-32
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    • 2005
  • The accuracy of exit poll mainly depends on the sampling method of voting places. For exit poll, we propose a probability sampling method of selecting voting places as an alternative to the bellwether polling place sampling. Through an empirical study based on the 2004 general election data, the efficiency of the suggested systematic sampling from ordered voting places was evaluated in terms of mean prediction error and it turns out that the proposed sampling method outperformed the bellwether polling places sampling. We also calculated the variance of estimator from the proposed sampling, and considered the sample size problem to guarantee the target precision using the design effect of the proposed sample design.

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Application of Multi-Dimensional Precipitation Models to the Sampling Error Problem (관측오차문제에 대한 다차원 강우모형의 적용)

  • Yu, Cheol-Sang
    • Journal of Korea Water Resources Association
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    • v.30 no.5
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    • pp.441-447
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    • 1997
  • Rainfall observation using rain gage network or satellites includes the sampling error depending on the observation methods or plans. For example, the sampling using rain gages is continuous in time but discontinuous in space, which is nothing but the source of the sampling error. The sampling using satellites is the reverse case that continuous in space and discontinuous in time. The sampling error may be quantified by use of the temporal-spatial characteristics of rainfall and the sampling design. One of recent works on this problem was done by North and Nakamoto (1989), who derived a formulation for estimating the sampling error based on the temporal-spatial rainfall spectrum and the design scheme. The formula enables us to design an optimal rain gage network or a satellite operation plan providing the statistical characteristics of rainfall. In this paper the formula is reviewed and applied for the sampling error problems using several multi-dimensional precipitation models. The results show the limitation of the formulation, which cannot distinguish the model difference in case the model parameters can reproduce similar second order statistics of rainfall. The limitation can be improved by developing a new way to consider the higher order statistics, and eventually the probability density function (PDF) of rainfall.

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SAMPLING ERROR ANALYSIS FOR SOIL MOISTURE ESTIMATION

  • Kim, Gwang-Seob;Yoo, Chul-sang
    • Water Engineering Research
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    • v.1 no.3
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    • pp.209-222
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    • 2000
  • A spectral formalism was applied to quantify the sampling errors due to spatial and/or temporal gaps in soil moisture measurements. The lack of temporal measurements of the two-dimensional soil moisture field makes it difficult to compute the spectra directly from observed records. Therefore, the space-time soil moisture spectra derived by stochastic models of rainfall and soil moisture was used in their record. Parameters for both models were tuned with Southern Great Plains Hydrology Experiment(SGP'97) data and the Oklahoma Mesonet data. The structure of soil moisture data is discrete in space and time. A design filter was developed to compute the sampling errors for discrete measurements in space and time. This filter has the advantage in its general form applicable for all kinds of sampling designs. Sampling errors of the soil moisture estimation during the SGP'97 Hydrology Experiment period were estimated. The sampling errors for various sampling designs such as satedlite over pass and point measurement ground probe were estimated under the climate condition between June and August 1997 and soil properties of the SGP'97 experimental area. The ground truth design was evaluated to 25km and 50km spatial gap and the temporal gap from zero to 5 days.

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An Improved Sample Design for Estimating the Usage of Copyrighted Music Works (노래연습장, 유흥·단란주점의 음악저작물이용 실태조사 개선안 연구)

  • Lee, Kay-O;Chung, Yeon-Soo
    • Communications for Statistical Applications and Methods
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    • v.19 no.3
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    • pp.315-331
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    • 2012
  • In this research, we estimated the number of hits per song and its sampling error from 11 (areas including Gangnam) based on log data compiling the number of hits collected from offline karaoke players in March 2011. Then, we calculated the monetary equivalent of the sampling error under the current system that distribute royalties from the karaoke players to copyright holders(song writers and arrangers) according to the estimated hits. Because of the small sample size, the estimated number of hits had a very large sampling error. This research proposes a more reasonable sample design to estimate the usage of copyrighted music works for a fair distribution of royalties by reducing sampling error.

The Effect of Sampling Rate on Statistical Properties of Extreme Wave (파랑자료의 sampling rate가 극한파의 통계에 미치는 영향)

  • Kim, Do Young
    • Journal of the Korean Society for Marine Environment & Energy
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    • v.16 no.1
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    • pp.36-41
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    • 2013
  • In this paper time series wave data are simulated using wave spectrum with random phases of the wave signal. The simulated wave signals are used to study the effect of the sampling rate on the ocean wave characteristics. Effect of sampling rate on wave data which include extreme wave such as freak waves are examined and various wave characteristics including abnormality index (AI), kurtosis of wave profile and maximum wave height are examined. Various wave heights are decreased as the sampling rate decreases. The zero-th moment of the wave spectrum does not affect much on the sampling rate but the second moment are greately affected on the sampling rate. The error due to the sampling rate is decreases as the wave period increases. The error in significant wave height based on the wave spectrum $H_s$ is smaller than that on the time domain method $H_{1/3}$. AI index and kurtosis of wave profile do not deviate much from the exact date as long as the sampling rate is greater than 1 Hz. Ocean wave measurement with the sampling frequency higher than 1 Hz will result the error less than 5% in estimating the height of extreme waves.

Hybrid Group-Sequential Conditional-Bayes Approaches to the Double Sampling Plans

  • Seong-gon Ko
    • Communications for Statistical Applications and Methods
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    • v.5 no.1
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    • pp.107-120
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    • 1998
  • This research aims here to develop a certain extended double sampling plan, EDS, which is an extension of ordinary double sampling plan in the sense that the second-stage sampling effort and second-stage critical value are allowed to depend on the point at which the first-stage continuation region is traversed. For purpose of comparison, single sampling plan, optimal ordinary double sampling plan(ODS) and sequential probability ratio test are considered with the same overall error rates, respectively. It is observed that the EDS idea allows less sampling effort than the optimal ODS.

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Determination of Sampling Unit Size for Cultivation Area Survey using Remote Sensing Technology

  • Park, Jin-Woo;Shin, Gi-Eun;Lee, Suk-Hoon;Byun, Jong-Seok
    • The Korean Journal of Applied Statistics
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    • v.25 no.5
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    • pp.733-741
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    • 2012
  • The successful launch of Arirang satellites allow the acquisition of high resolution satellite imagery of Korean territory and enables the transition from the conventional cultivation area survey method to new image based methods adopted in advanced nations. In this study, we suggested reasonable sizes of the primary sampling unit and the secondary sampling unit for the satellite imagery based sampling design in 8 provinces preselected for this research. The PSU size was determined mainly in consideration of intracorrelation that shows the degree of homogeneity within each cluster and the efficiency of the image process. For the SSU size, we considered the relative standard error and the differences between the land cover maps produced by the Ministry of Environment and the satellite imagery processed by the National Statistical Office.

An Integrated Sequential Inference Approach for the Normal Mean

  • Almahmeed, M.A.;Hamdy, H.I.;Alzalzalah, Y.H.;Son, M.S.
    • Journal of the Korean Statistical Society
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    • v.31 no.4
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    • pp.415-431
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    • 2002
  • A unified framework for statistical inference for the mean of the normal distribution to derive point estimates, confidence intervals and statistical tests is proposed. This optimal design is justified after investigating the basic information and requirements that are possible and impossible to control when specifying practical and statistical requirements. Point estimation is only credible when viewed in the larger context of interval estimation, since the information required for optimal point estimation is unspecifiable. Triple sampling is proposed and justified as a reasonable sampling vehicle to achieve the specifiable requirements within the unified framework.