Assessment and Estimation of the Coefficients of a Linear Model for Interval Data

Imprecise measurement tools produce imprecise data. Interval,-valued (interval) data is ‌one type of data ‌which is usually ‌used to deal with such imprecision. So,‌ interval-valued variables have been used in the last decade. The relationships between the variables have recently ‌been modeled by linear regression models. If interval response variables have any statistical distributions, the relationships are ‌modeled in the linear models framework. In this paper, we propose new estimators for the parameters of an interval linear model under some conditions. Under the conditions, we demonstrate the theoretical adequacy of the estimators. Simulation studies and a real-life case study show the empirical adequacy and the practical applicability of the new estimators, respectively, under the conditions.