Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/14733| Title: | Lasso estimation of an interval-valued multiple regression model |
| Authors: | Bárzana, Marta García Colubi, Ana Kontoghiorghes, Erricos John |
| metadata.dc.contributor.other: | Κοντογιώργης, Ερρίκος |
| Major Field of Science: | Social Sciences |
| Field Category: | Economics and Business |
| Keywords: | Interval-valued data;Lasso estimation;Multiple regression;Constraint theory |
| Issue Date: | 1-Jan-2015 |
| Source: | Advances in Intelligent Systems and Computing Volume 315, 2015, Pages 185-191 |
| Volume: | 315 |
| Journal: | Advances in Intelligent Systems and Computing |
| Abstract: | © Springer International Publishing Switzerland 2015. A multiple interval-valued linear regression model considering all the cross-relationships between the mids and spreads of the intervals has been introduced recently. A least-squares estimation of the regression parameters has been carried out by transforming a quadratic optimization problem with inequality constraints into a linear complementary problem and using Lemke’s algorithm to solve it. Due to the irrelevance of certain cross-relationships, an alternative estimation process, the LASSO (Least Absolut Shrinkage and Selection Operator), is developed. A comparative study showing the differences between the proposed estimators is provided. |
| URI: | https://hdl.handle.net/20.500.14279/14733 |
| ISSN: | 21945357 |
| DOI: | 10.1007/978-3-319-10765-3_22 |
| Rights: | © Springer International Publishing 2015. |
| Type: | Article |
| Affiliation : | University of Oviedo Cyprus University of Technology |
| Publication Type: | Peer Reviewed |
| Appears in Collections: | Άρθρα/Articles |
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