Imputation strategy with media using regression trees
An imputation design is presented to combine classication and imputation in order to improve the quality of imputed datum. Imputation is done with completely randomized missing quantitative data and using regression trees. Media imputation techniques is compared, theoretical and empirically, using...
| Autor Principal: | Marquez Perez, Victor Ernesto |
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| Otros Autores: | Useche Castro, Lelly María, Mesa Avila, Dulce María, Chacon Contreras, Ana Ides |
| Formato: | info:eu-repo/semantics/article |
| Idioma: | spa |
| Publicado: |
Universidad Santo Tomás
2017
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| Materias: | |
| Acceso en línea: |
http://revistas.usta.edu.co/index.php/estadistica/article/view/2524 |
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| Sumario: |
An imputation design is presented to combine classication and imputation in order to improve the quality of imputed datum. Imputation is done with completely randomized missing quantitative data and using regression trees. Media imputation techniques is compared, theoretical and empirically, using regression trees, in order to develop an integral classication and imputation strategy.Unbiased estimators were obtained developing the expected value of the estimator. Estimators proprieties were evaluated trough their variance and bias development, which showed non bias. as for the unbiased estimator variance of the media, suficiency was not proved for the media estimator. |
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