Calibrated bayesian shrinkage of finite population totals in survey sampling
In this article a Bayesian methodology (parametric and nonparametric) is proposed in order to estimate, by means of calibration, the population total from a sample with unequal inclusion probabilities. By means of some simulation studies, it was empirically determined that, through an adequate ch...
| Autor Principal: | Gutiérrez, Andrés |
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| Otros Autores: | Zhang, Hanwen, Tellez, Cristian, Guerrero, Stalyn |
| Formato: | Generación de Nuevo Conocimiento: Artículos publicados en revistas especializadas - Electrónicos |
| Publicado: |
2019
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| Materias: | |
| Acceso en línea: |
Gutiérrez, A., Zhang, H., Tellez, C., & Guerrero, S. (2018). Calibrated bayesian shrinkage of finite population totals in survey sampling doi:10.1080/09720510.2017.1367477 |
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| Sumario: |
In this article a Bayesian methodology (parametric and nonparametric) is proposed in
order to estimate, by means of calibration, the population total from a sample with unequal
inclusion probabilities. By means of some simulation studies, it was empirically determined
that, through an adequate choice of an prior distribution with the proposed methodology,
unbiased estimators are obtained. In addition to this, with an appropriate sample size, a
smaller variance and confidence intervals with higher levels and minor length were obtained
in comparison with the intervals induced by classic estimators (Horvitz-Thompson and
calibration estimators). Finally, the implementation of the methodology to estimate the
income is exemplified using real data from a labor force survey in Colombia. |
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