A linear regression model for interval-valued response based on set arithmetic. (English) Zbl 06580225

Kruse, Rudolf (ed.) et al., Synergies of soft computing and statistics for intelligent data analysis. Papers based on the presentations at the 6th international conference on soft methods and probability and statistics, SMPS, Konstanz, Germany, October 4–6, 2012. Berlin: Springer. Adv. Intell. Syst. Comput. 190, 105-113 (2013).
Summary: Several linear regression models involving interval-valued variables have been formalized based on the interval arithmetic. In this work, a new linear regression model with interval-valued response and real predictor based on the interval arithmetic is formally described. The least-squares estimation of the model is solved by means of a constrained minimization problem which guarantees the coherency of the estimators with the regression parameters. The practical applicability of the estimation method is checked on a real-life example, and the empirical behaviour of the procedure is shown by means of some simulation studies.
For the entire collection see [Zbl 1312.68013].


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