• 제목/요약/키워드: Finite population

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Robust Bayesian Inference in Finite Population Sampling under Balanced Loss Function

  • Kim, Eunyoung;Kim, Dal Ho
    • Communications for Statistical Applications and Methods
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    • 제21권3호
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    • pp.261-274
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    • 2014
  • In this paper we develop Bayes and empirical Bayes estimators of the finite population mean with the assumption of posterior linearity rather than normality of the superpopulation under the balanced loss function. We compare the performance of the optimal Bayes estimator with ones of the classical sample mean and the usual Bayes estimator under the squared error loss with respect to the posterior expected losses, risks and Bayes risks when the underlying distribution is normal as well as when they are binomial and Poisson.

Bayesian inference in finite population sampling under measurement error model

  • Goo, You Mee;Kim, Dal Ho
    • Journal of the Korean Data and Information Science Society
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    • 제23권6호
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    • pp.1241-1247
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    • 2012
  • The paper considers empirical Bayes (EB) and hierarchical Bayes (HB) predictors of the finite population mean under a linear regression model with measurement errors We discuss how to calculate the mean squared prediction errors of the EB predictors using jackknife methods and the posterior standard deviations of the HB predictors based on the Markov Chain Monte Carlo methods. A simulation study is provided to illustrate the results of the preceding sections and compare the performances of the proposed procedures.

A Generalized Ratio-cum-Product Estimator of Finite Population Mean in Stratified Random Sampling

  • Tailor, Rajesh;Sharma, Balkishan;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • 제18권1호
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    • pp.111-118
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    • 2011
  • This paper suggests a ratio-cum product estimator of a finite population mean using information on the coefficient of variation and the fcoefficient of kurtosis of auxiliary variate in stratified random sampling. Bias and MSE expressions of the suggested estimator are derived up to the first degree of approximation. The suggested estimator has been compared with the combined ratio estimator and several other estimators considered by Kadilar and Cingi (2003). In addition, an empirical study is also provided in support of theoretical findings.

Families of Estimators of Finite Population Variance using a Random Non-Response in Survey Sampling

  • Singh, Housila P.;Tailor, Rajesh;Kim, Jong-Min;Singh, Sarjinder
    • 응용통계연구
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    • 제25권4호
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    • pp.681-695
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    • 2012
  • In this paper, a family of estimators for the finite population variance investigated by Srivastava and Jhajj (1980) is studied under two different situations of random non-response considered by Tracy and Osahan (1994). Asymptotic expressions for the biases and mean squared errors of members of the proposed family are obtained; in addition, an asymptotic optimum estimator(AOE) is also identified. Estimators suggested by Singh and Joarder (1998) are shown to be members of the proposed family. A correction to the Singh and Joarder (1998) results is also presented.

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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    • 제10권2호
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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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Robust Bayesian inference in finite population sampling with auxiliary information under balanced loss function

  • Kim, Eunyoung;Kim, Dal Ho
    • Journal of the Korean Data and Information Science Society
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    • 제25권3호
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    • pp.685-696
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    • 2014
  • In this paper, we develop Bayesian inference of the finite population mean with the assumption of posterior linearity rather than normality of the superpopulation in the presence of auxiliary information under the balanced loss function. We compare the performance of the optimal Bayes estimator under the balanced loss function with ones of the classical ratio estimator and the usual Bayes estimator in terms of the posterior expected losses, risks and Bayes risks.

Efficient Use of Auxiliary Variables in Estimating Finite Population Variance in Two-Phase Sampling

  • Singh, Housila P.;Singh, Sarjinder;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • 제17권2호
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    • pp.165-181
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    • 2010
  • This paper presents some chain ratio-type estimators for estimating finite population variance using two auxiliary variables in two phase sampling set up. The expressions for biases and mean squared errors of the suggested c1asses of estimators are given. Asymptotic optimum estimators(AOE's) in each class are identified with their approximate mean squared error formulae. The theoretical and empirical properties of the suggested classes of estimators are investigated. In the simulation study, we took a real dataset related to pulmonary disease available on the CD with the book by Rosner, (2005).

유한모집단의 신제품 품질평가를 위한 소표본 샘플링검사 방법에 대한 소고 (A Study on Small-Sample Inspection Plan for New Product Quality Evaluation of Finite Population)

  • 변재현;신병철;이창우
    • 대한산업공학회지
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    • 제41권1호
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    • pp.115-120
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    • 2015
  • Evaluating product quality level is necessary before the manufactured items are delivered to the customer. When the amount of the items to be manufactured is limited and the product is of high price and should be evaluated by destructive testing, the number of samples to be tested should be as small as possible. This paper presents a small-sample inspection method using hyper-geometric distribution and Bayesian approach for finite small-sized population. A method of determining the minimum sample size is presented for given population size, allowable number of defectives, warranteed defective level, and confidence level which is the degree of confidence on the product quality level recognized by both the producer and the customer.

Ratio and Product Type Exponential Estimators of Population Mean in Double Sampling for Stratification

  • Tailor, Rajesh;Chouhan, Sunil;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • 제21권1호
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    • pp.1-9
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    • 2014
  • This paper discusses the problem of estimation of finite population mean in double sampling for stratification. In fact, ratio and product type exponential estimators of population mean are proposed in double sampling for stratification. The biases and mean squared errors of proposed estimators are obtained upto the first degree of approximation. The proposed estimators have been compared with usual unbiased estimator, ratio and product estimators in double sampling for stratification. To judge the performance of the proposed estimators an empirical study has been carried out.

Bayesian Analysis under Heavy-Tailed Priors in Finite Population Sampling

  • Kim, Dal-Ho;Lee, In-Suk;Sohn, Joong-Kweon;Cho, Jang-Sik
    • Communications for Statistical Applications and Methods
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    • 제3권3호
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    • pp.225-233
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    • 1996
  • In this paper, we propose Bayes estimators of the finite population mean based on heavy-tailed prior distributions using scale mixtures of normals. Also, the asymptotic optimality property of the proposed Bayes estimators is proved. A numerical example is provided to illustrate the results.

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