• Title/Summary/Keyword: Random Sample

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A Note on the Decision of Sample Size by Relative Standard Error in Successive Occasions (계속조사에서 상대표준오차를 이용한 표본크기 결정에 관한 고찰)

  • Han, GeunShik;Lee, Gi-Sung
    • The Korean Journal of Applied Statistics
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    • v.28 no.3
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    • pp.477-483
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    • 2015
  • This study deals with the decision problem of sample size by the relative standard error of estimates derived from survey results in successive occasions. The population of the construction in business survey results is used to calculate quartile of the relative standard error of the 1,000 sample obtained from simple or stratified random sampling. The sample size at time t with a relative standard error of the point (t-1) in the successive occasions were calculated according to the sampling method. As a result, in terms of the sample size according to the size of the relative standard error of the (t-1), simple random sampling differs significantly from stratified sampling. In addition, we could see differences in sample size (depending on how the population is stratified) and that careful attention is required in the problem of sample size by the relative standard error of estimates derived from survey results in successive occasions.

RDD Sample versus Directory - Based Sample for Telephone Surveys: The Case of 2007 Presidential Election Forecasting in Korea (RDD 표본 대 전화번호부 표본: 2007년 대통령 선거 예측사례)

  • Huh, Myung-Hoe;Kim, Young-Won
    • Survey Research
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    • v.9 no.3
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    • pp.55-69
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    • 2008
  • In most telephone surveys in Korea, telephone numbers are selected from the directories. Inevitably, such samples may lack representativeness due to poor coverage rate. To resolve the problem, Kang et al.(2008) implemented RDD(random digit dialing) method for nationwide sampling in Korea. The aim of this study is to compare an RDD sample with a traditional telephone quota sample that were collected independently by two survey institutes commissioned by the KBS-MBC consortium for the 2007 Presidential Election of Korea.

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Camera Source Identification of Digital Images Based on Sample Selection

  • Wang, Zhihui;Wang, Hong;Li, Haojie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.7
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    • pp.3268-3283
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    • 2018
  • With the advent of the Information Age, the source identification of digital images, as a part of digital image forensics, has attracted increasing attention. Therefore, an effective technique to identify the source of digital images is urgently needed at this stage. In this paper, first, we study and implement some previous work on image source identification based on sensor pattern noise, such as the Lukas method, principal component analysis method and the random subspace method. Second, to extract a purer sensor pattern noise, we propose a sample selection method to improve the random subspace method. By analyzing the image texture feature, we select a patch with less complexity to extract more reliable sensor pattern noise, which improves the accuracy of identification. Finally, experiment results reveal that the proposed sample selection method can extract a purer sensor pattern noise, which further improves the accuracy of image source identification. At the same time, this approach is less complicated than the deep learning models and is close to the most advanced performance.

Large Sample Test for Independence in the Bivariate Pareto Model with Censored Data

  • Cho, Jang-Sik;Lee, Jea-Man;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.2
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    • pp.377-383
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    • 2003
  • In this paper, we consider two components system in which the lifetimes follow the bivariate Pareto model with random censored data. We assume that the censoring time is independent of the lifetimes of the two components. We develop large sample tests for testing independence between two components. Also we present simulated study which is the test based on asymptotic normal distribution in testing independence.

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THE LIMITING SPECTRAL DISTRIBUTION FUNCTION OF LARGE DIMENSIONAL RANDOM MATERICES OF SAMPLE COVARIANCE TYPE

  • Choi, Sang-Il
    • Journal of applied mathematics & informatics
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    • v.5 no.2
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    • pp.465-474
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    • 1998
  • Results on the analytic behavior to the limiting spectral distribution of matrices of sample convariance type. studied in Marcenko and Pastur [2] are derived. using the Stieltjes transform it is shown that the limiting distrbution has a continuous derivative away from zero the derivative being analytic whenever it is positive and the behavior of it resembles the behavior of a square root function near the boundary of its support.

Nonresponse in Repeated Surveys

  • Park, Hyeon-Ah;Na, Seong-Ryong;Jeon, Jong-Woo
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.593-600
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    • 2007
  • Under repeated surveys, missing values often appear for various reasons and are replaced by new samples. It is investigated that the existing estimator in repeated survey by Jessen (1942), which has been originally developed for the new samples of fixed size, can be used in such situation where the size of new samples is random. It is shown that the proposed estimator has smaller variance than the sample mean.

Simulation of Multi-Variate Random Processes (다변수 확률과정의 시뮬레이션)

  • ;M. Shinozuka
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1990.04a
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    • pp.24-30
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    • 1990
  • An improved algorithm for simulation of multi-variate random processes has been presented. It is based on the spectral representation method. The conventional methods give sample time histories which satisfy the target spectral density matrix only in the sense of ensemble average. However, the present method can generate sample functions which satisfy the target spectra in the ergodic sense. Example analysis is given for the simulation of earthquake accelerations with three components.

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Stochastic Comparisons of Order Statistics

  • Kim, Song-Ho
    • Journal of the Korean Statistical Society
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    • v.22 no.1
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    • pp.13-25
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    • 1993
  • The purpose of this paper is to investigate the properties of order statistics under various stochastic relations. We study the stochastic comparison of order statistics in a single sample. And we consider two sample case too. For example, F(t) > G9t) for t > 0 when X and Y are random variables symmetric about 0, with c.d.f.s F and G. Two examples are provided.

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Ranked-Set Sample Wilcoxon Signed Rank Test For Quantiles Under Equal Allocation

  • Kim, Dong Hee;Kim, Hyun Gee
    • Communications for Statistical Applications and Methods
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    • v.10 no.2
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    • pp.535-543
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    • 2003
  • A ranked set sample version of the sign test is proposed for testing hypotheses concerning the quantiles of a population characteristic by Kaur, et. al(2002). In this paper, we proposed the ranked set sample Wilcoxon signed rank test for quantiles under equal allocation. We obtain the asymptotic property and the asymptotic relative efficiencies of the proposed test statistic with respect to Wilcoxon signed rank test of simple random sample for quantiles under equal allocation. We calculate the ARE of test statistics, the proposed test statistic is more efficient than simple random sampling for all quantiles. The relative advantage of ranked set sampling is greatest at the median and tapers off in the tails.

Nonparametric Test for Ordered Alternatives on Multiple Ranked-Set Samples

  • Kim, Dong HeeKim,;Hyung Gee;Park, Hae Kyung
    • Communications for Statistical Applications and Methods
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    • v.7 no.2
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    • pp.563-573
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    • 2000
  • In this thesis, we propose the test statistic for ordered alternatives on c-sample ranked set samples(RSS). The proposed test statistic JRSS is Jonckheere type statistic using the median of the i-th samples in each cycle. We obtained the asymptotic property of the proposed test statistic and the asymptotic relative efficiencies of the proposed test statistic with respect to J SRS which Jonckheere type statistic on simple random samples(SRS). From the simulation works, J RSS is superior to J SRS. We compared the empirical powers of J RSS with respect to U RSS on ranked set sample and U SRS on simple random sample using all samples, which are proposed by Kim, Kim and Lee(1999). The powers of J RSS are nearly the same values when entire sample size is large. J RSS is superior to U RSS. J RSS is simpler than U RSSon calculating process.

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