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Imputation strategy with media using regression trees
| dc.contributor.author | Marquez Perez, Victor Ernesto | spa |
| dc.contributor.author | Useche Castro, Lelly María | spa |
| dc.contributor.author | Mesa Avila, Dulce María | spa |
| dc.contributor.author | Chacon Contreras, Ana Ides | spa |
| dc.date.issued | 2017-05-16 | spa |
| dc.identifier | https://revistas.usantotomas.edu.co/index.php/estadistica/article/view/2524 | spa |
| dc.identifier | 10.15332/s2027-3355.2017.0001.01 | spa |
| dc.description | An imputation design is presented to combine classification 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 classification and imputation strategy.Unbiased estimators were obtained developing the expected value of the estimator. Estimator’s proprieties were evaluated trough their variance and bias development, which showed non bias. as for the unbiased estimator variance of the media, sufficiency was not proved for the media estimator. | spa |
| dc.description | 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. | eng |
| dc.format.mimetype | application/pdf | spa |
| dc.format.mimetype | application/octet-stream | spa |
| dc.language.iso | spa | spa |
| dc.publisher | Universidad Santo Tomás | spa |
| dc.relation | https://revistas.usantotomas.edu.co/index.php/estadistica/article/view/2524/3533 | spa |
| dc.relation | https://revistas.usantotomas.edu.co/index.php/estadistica/article/view/2524/3567 | spa |
| dc.rights | Copyright (c) 2017 Comunicaciones en Estadística | spa |
| dc.title | Imputation strategy with media using regression trees | spa |
| dc.title.alternative | Imputation strategy with media using regression trees | eng |
| dc.type.version | info:eu-repo/semantics/publishedVersion | |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
| dc.subject.proposal | missing data; imputation; CART; regression trees; unbiased estimators; simulation | spa |
| dc.subject.proposal | Missing data; imputation; CART; regression trees; unbiased estimators; simulation. | eng |
| dc.type.drive | info:eu-repo/semantics/article | |
| dc.relation.citationissue | Comunicaciones en Estadística; Vol. 10, Núm. 1 (2017); 9-40 | spa |
| dc.relation.citationissue | Comunicaciones en Estadística; Vol. 10, Núm. 1 (2017); 9-40 | eng |
| dc.relation.citationissue | 2339-3076 | spa |
| dc.relation.citationissue | 2027-3355 | spa |
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