A Comparison of Hierarchical Bayesian Models for Small Area Estimation of Counts
作者: Matilde TrevisaniNicola Torelli
刊名: Open Journal of Statistics, 2017, Vol.7 (3), pp.521-550
来源数据库: Scientific Research Publishing Journal
DOI: 10.4236/ojs.2017.73036
原始语种摘要: Small area estimation (SAE) tackles the problem of providing reliable estimates for small areas, i.e. , subsets of the population for which sample information is not sufficient to warrant the use of a direct estimator. Hierarchical Bayesian approach to SAE problems offers several advantages over traditional SAE models including the ability of appropriately accounting for the type of surveyed variable. In this paper, a number of model specifications for estimating small area counts are discussed and their relative merits are illustrated. We conducted a simulation study by reproducing in a simplified form the Italian Labour Force Survey and taking the Local Labor Markets as target areas. Simulated data were generated by assuming population characteristics of interest as well as survey...
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  • unemployment 失业
  • general 普遍的
  • nonnormal 非正规的
  • accounting 会计
  • ability 能力
  • estimating 价值估计
  • number 号码
  • stochastically 随机地
  • variable 变量
  • model 模型