Model-Assisted Survey Estimation with Modern Prediction Techniques

• Autores: F. Jay Breidt, Jean D. Opsomer
• Localización: Statistical science, ISSN 0883-4237, Vol. 32, Nº. 2, 2017, págs. 190-205
• Idioma: inglés
• DOI: 10.1214/16-sts589
• Texto completo no disponible (Saber más ...)
• Resumen

  • This paper reviews the design-based, model-assisted approach to using data from a complex survey together with auxiliary information to estimate finite population parameters. A general recipe for deriving modelassisted estimators is presented and design-based asymptotic analysis for such estimators is reviewed. The recipe allows for a very broad class of prediction methods, with examples from the literature including linear models, linear mixed models, nonparametric regression and machine learning techniques.