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A Synthesis of Objective Bayesian and Designed Based Methods for Finite Population Sampling

A Synthesis of Objective Bayesian and Designed Based Methods for Finite Population Sampling
客观贝叶斯综合和有限总体抽样设计方法
批准号:
0406169
负责人:
Glen Meeden
金额:
$0.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-07-01 至 2008-06-30

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ABSTRACTproposal: 0406169PI: Glen Meeden A synthesis of objective Bayesian and designed based methods for finite population sampling Project Abstract In the frequentist or design approach to finite population sampling priorinformation is incorporated in the sampling design. However in some cases when calculating estimates the design weights need to be readjusted, and then it can be difficult to find sensible estimates of variance.In the Bayesian approach prior information is incorporated througha prior distribution. Since the posterior distribution does not depend on the design it has been difficult to theoretically reconcile the two approaches. The Polya posterior is an objective Bayesian approach to finite population sampling that is appropriate when littleor no prior information is available. The investigator is developing a synthesis of this objective Bayesian approach and the designbased approach. It has two main threads. In the first the Polya posterior is extended to problems where it cannot be applied directly because of additional prior information contained in auxiliaryvariables. This leads to a constrained or restrictedversion of the Polya posterior. In the second Bayesian models aredeveloped which directly include the design in the specification of the prior. Such models are a generalization of the Polya posterior and using them one can objectively incorporate into a prior the same kind of information that is encapsulated in a design.The investigator is developing the underlying theory and methods tosimulate from these objective posteriors so that estimators can be found in practice and their frequentist properties studied. One of the most basic problems of statistics is making an inference about a population based on a sample collected from the population.When little is known about the population the mean of thevalues in a random sample is used as an estimate of the populationmean. However in addition to the estimate one also needs a sensible measure of its uncertainty or variance. In mostsituations there is prior information available about the population. This information should be used in deciding what units are to be included in the sample, the value of the estimate and the appropriate measure of uncertainty. The investigator is working on a synthesis of the two standard approaches to these problems. The results should make more effective use of available prior information than present methods.Because of the many surveys done each year by government and others improving survey practice is of great practical significance.
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A Noninformative Bayesian Approach to some Finite Population Problems when Auxiliary Variables are Present
  • 批准号:
    9971331
  • 项目类别:
    Standard Grant
  • 资助金额:
    $7.5万
  • 财政年份:
    1999
  • 负责人:
    Glen Meeden
  • 依托单位:
Mathematical Sciences: Some Bayesian Problems in Sample Survey
  • 批准号:
    9401191
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $6.0万
  • 财政年份:
    1994
  • 负责人:
    Glen Meeden
  • 依托单位:
Some Bayesian Methods for Sequences of Discrete Observationsand for Finite Population Sampling
  • 批准号:
    9201718
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $8.0万
  • 财政年份:
    1992
  • 负责人:
    Glen Meeden
  • 依托单位:
Mathematical Sciences: The Application of the Stepwise BayesTechnique to Some Statistical Questions
  • 批准号:
    8902580
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.71万
  • 财政年份:
    1989
  • 负责人:
    Glen Meeden
  • 依托单位:
海外基金