Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/9757
Title: | On the estimation of the regression model M for interval data |
Authors: | Garciá-Bárzana, Marta Colubi, Ana Kontoghiorghes, Erricos John |
Major Field of Science: | Social Sciences |
Field Category: | Economics and Business |
Keywords: | Interval data;Regression model |
Issue Date: | 2013 |
Source: | Towards advanced data analysis by combining soft computing and statistics, 2013, pp. 43-52 |
Abstract: | A linear regression model for interval data based on the natural interval-arithmetic has recently been proposed. Interval data can be identified with 2-dimensional points in ℝ x ℝ+, since they can be parametrized by its mid-point and its semi-amplitude or spread, which is non-negative. The model accounts separately for the contribution of the mid-points and the spreads through a single equation. The least squares estimation becomes a quadratic optimization problem subject to linear constraints, which guarantee the existence of the residuals. Several estimators are discussed. Namely, a closed-form estimator, the restricted least-squares estimator, an empirical estimator and an estimator based on separate models for mids and spreads have been investigated. Real-life examples are considered. Simulations are performed in order to assess the consistency and the bias of the estimators. Results indicate that the numerical and the closed-form estimator are appropriate in most of cases, while the empirical estimator and the one based on separate models are not always suitable. |
URI: | https://hdl.handle.net/20.500.14279/9757 |
ISBN: | 978-3-642-30278-7 |
DOI: | 10.1007/978-3-642-30278-7_4 |
Rights: | © Springer-Verlag 2013. |
Type: | Book Chapter |
Affiliation : | Universidad de Oviedo Australian Catholic University |
Publication Type: | Peer Reviewed |
Appears in Collections: | Κεφάλαια βιβλίων/Book chapters |
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