Quantile Model-Assisted estimation approach for the estimation of a population total
Abstract: A quantile model-assisted approach is used to estimate a finite population total. This estimator attempts to make efficient use of auxiliary Information under the presence of influential points. The approach consists in minimizing a weighted sum of the distances between fitted and observed...
- Autores:
-
Zea Castro, José Fernando
- Tipo de recurso:
- Fecha de publicación:
- 2012
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/62963
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/62963
http://bdigital.unal.edu.co/62322/
- Palabra clave:
- 31 Colecciones de estadística general / Statistics
51 Matemáticas / Mathematics
Quantile regression
Generalized regression estimation
Model-Assisted survey
Sampling
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | Abstract: A quantile model-assisted approach is used to estimate a finite population total. This estimator attempts to make efficient use of auxiliary Information under the presence of influential points. The approach consists in minimizing a weighted sum of the distances between fitted and observed values. Firstly, an estimator for population coefficients of a quantile regression is obtained, then a GREG-like estimator for the total Is presented. The performance of the proposed estimator is assessed empirically via simulation studies under scenarios such as: different distribution of the errors and distinct settings of extreme observations with a single auxiliary variable. The proposed estimator for the finite population total seems to have a good performance in terms of smaller bias and mean square error specially in skewed distribution, normal mixtures and in the presence of influential points. |
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