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arXiv · 1602.02408

Lasso Estimation of an Interval-Valued Multiple Regression Model

Marta García Bárzana·Ana Colubi·Erricos John Kontoghiorghes
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Abstract

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.

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Marta García Bárzana, Ana Colubi, Erricos John Kontoghiorghes. 2016-02-07. Lasso Estimation of an Interval-Valued Multiple Regression Model. https://arxiv.org/abs/1602.02408

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