Interval arithmetic-based simple linear regression between interval data: Discussion and sensitivity analysis on the choice of the metric

  • Authors:
  • Beatriz Sinova;Ana Colubi;Marıa Ángeles Gil;Gil González-Rodrıguez

  • Affiliations:
  • Departamento de Estadıstica, I.O. y D.M., Universidad de Oviedo, 33071 Oviedo, Spain;Departamento de Estadıstica, I.O. y D.M., Universidad de Oviedo, 33071 Oviedo, Spain;Departamento de Estadıstica, I.O. y D.M., Universidad de Oviedo, 33071 Oviedo, Spain;Departamento de Estadıstica, I.O. y D.M., Universidad de Oviedo, 33071 Oviedo, Spain

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2012

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Abstract

The prediction of a response random interval-valued set from an explanatory one has been examined in previous developments. These developments have considered an interval arithmetic-based linear model between the random interval-valued sets and a least squares regression analysis. The least squares approach involves a generalized L"2-metric between interval data; this metric weights squared distances between data location (mid-points/centers) and squared distances between data imprecision (spread/radius). As a consequence, estimators of the parameters in the linear model depend on the choice of the weights in the metric. To investigate about a suitable choice of weighting in the generalized mid/spread metric, a theoretical conclusion is first obtained. Finally, the impact of varying the weights is discussed by considering a Monte Carlo simulation study.