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Prediction of the nonsampled units in survey design with the finite population using Bayesian nonparametric mixture model
Communications in Statistics - Simulation and Computation ( IF 0.9 ) Pub Date : 2020-04-09 , DOI: 10.1080/03610918.2019.1710190
S. Rahnamay Kordasiabi 1 , S. Khazaei 1
Affiliation  

Abstract

In the sampling approaches framework, the combination of the information on the sizes of the nonsampled units can help to attain better estimators by using semiparametric models. Sometimes, the design variables that have an important role in the sampling mechanism are not available. Hence predictions require to be adapted for the consequence of selection. To infer the population mean in a sample survey, we study Bayesian nonparametric model with Dirichlet process prior by considering the inverse-probability weights as the only available information. Indeed, we present a Bayesian nonparametric mixture of regression models for the survey outcomes with the weights as predictors and impute the nonsampled units. Finally, the model-based estimators that are derived from the Bayesian (parametric and nonparametric) methods are compared with the design-based estimator based on the simulation approaches.



中文翻译:

使用贝叶斯非参数混合模型预测有限总体调查设计中的非抽样单位

摘要

在抽样方法框架中,非抽样单位大小信息的组合有助于通过使用半参数模型获得更好的估计量。有时,在抽样机制中起重要作用的设计变量不可用。因此,预测需要适应选择的结果。为了推断样本调查中的总体均值,我们通过将逆概率权重作为唯一可用信息来研究具有 Dirichlet 过程的贝叶斯非参数模型。实际上,我们为调查结果提出了贝叶斯非参数混合回归模型,其中权重作为预测变量,并估算了非抽样单位。最后,

更新日期:2020-04-09
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