Off the beaten track: A new linear model for interval data

• Type: Article in International Scientific Journal
• Date: 2017

Authors

Dias, S (Author) Other; brito, p (Author) FEP

Journal

Title: European Journal of Operational Research

Vol. 258

Pages: 1118-1130

ISSN: 0377-2217

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 34 Citations

Scopus - 35 Citations

Other information

Authenticus ID: P-00M-CZN

DOI: 10.1016/j.ejor.2016.09.006

Abstract (EN): We propose a new linear regression model for interval-valued variables. The model uses quantile functions to represent the intervals, thereby considering the distributions within them. In this paper we study the special case where the Uniform distribution is assumed in each observed interval, and we analyze the extension to the Symmetric Triangular distribution. The parameters of the model are obtained solving a constrained quadratic optimization problem that uses the Mallows distance between quantile functions. As in the classical case, a goodness-of-fit measure is deduced. Two applications on up-to-date fields are presented: one predicting duration of unemployment and the other allowing forecasting burned area by forest fires.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13