Abstract
The objective of this paper is to build a regression model with
confidence intervals where such confidence intervals are expressed
through the expectations and variances of fuzzy random variables.
First, a general regression model for fuzzy random data is
introduced. Then, using expectations and variances of fuzzy random
variables, a regression model with confidence intervals is
established. Given the nature of such modeling, we will be referring
to these models as fuzzy random regression models with confidence
intervals. The proposed regression model gives rise to non-linear
programming consisting of the productions between involving fuzzy
numbers or interval numbers. The inherent non-linearity of the
optimization makes it hard to exploit techniques of linear
programming and we need to resort ourselves to some heuristics.
Lastly, an illustrative example is provided.
