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An Exact Algorithm for Likelihood-Based Imprecise Regression in the Case of Simple Linear Regression with Interval Data

  • Andrea Wiencierz
  • Marco E. G. V. Cattaneo
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 190)

Abstract

Likelihood-based Imprecise Regression (LIR) is a recently introduced approach to regression with imprecise data. Here we consider a robust regression method derived from the general LIR approach and we establish an exact algorithm to determine the set-valued result of the LIR analysis in the special case of simple linear regression with interval data.

Keywords

Interval data likelihood inference robust regression 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of StatisticsLMU MunichMünchenGermany

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