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. © 2013 Springer-Verlag.
CITATION STYLE
Blanco-Fernández, A., Colubi, A., García-Bárzana, M., & Montenegro, M. (2013). A linear regression model for interval-valued response based on set arithmetic. In Advances in Intelligent Systems and Computing (Vol. 190 AISC, pp. 105–113). Springer Verlag. https://doi.org/10.1007/978-3-642-33042-1_12
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