• Title/Summary/Keyword: Superpopulation models

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The Decision of Critical Population Size for Releasing Micro Data Files (마이크로데이터 제공에 따른 임계모집단 크기 결정)

  • NamKung, Pyong;So, Joung-Hyun
    • Communications for Statistical Applications and Methods
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    • v.17 no.6
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    • pp.791-801
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    • 2010
  • This study reviews the concept of disclosure, disclosure risks, and uniqueness. The number of uniqueness in the population is of great importance in evaluating the disclosure risk of micro data files. We approach this problem by considering some basic superpopulation models including the Multinomial-Dirichlet model, the Poisson- Gamma model of Bethlehem et al. (1990) and Takemura (1997), and the Modified Multinomial-Dirichlet model. We decided the critical population size of each superpopulation model for four different superpopulation models.

Bayesian Prediction under Dynamic Generalized Linear Models in Finite Population Sampling

  • Dal Ho Kim;Sang Gil Kang
    • Communications for Statistical Applications and Methods
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    • v.4 no.3
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    • pp.795-805
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    • 1997
  • In this paper, we consider a Bayesian forecasting method for the analysis of repeated surveys. It is assumed that the parameters of the superpopulation model at each time follow a stochastic model. We propose Bayesian prediction procedures for the finite population total under dynamic generalized linear models. Some numerical studies are provided to illustrate the behavior of the proposed predictors.

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Finite Population Prediction under Multiprocess Dynamic Generalized Linear Models

  • Kim, Dal-Ho;Cha, Young-Joon;Lee, Jae-Man
    • Journal of the Korean Data and Information Science Society
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    • v.10 no.2
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    • pp.329-340
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    • 1999
  • We consider a Bayesian forcasting method for the analysis of repeated surveys. It is assumed that the parameters of the superpopulation model at each time follow a stochastic model. We propose Bayesian prediction procedures for the finite population total under multiprocess dynamic generalized linear models. The multiprocess dynamic model offers a powerful framework for the modelling and analysis of time series which are subject to a abrupt changes in pattern. Some numerical studies are provided to illustrate the behavior of the proposed predictors.

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