A linear regression model with fuzzy Neutrosophic data

Statistical regression analysis is a well-known method for formulating the relationship between the response variable (output) and some explanatory variables (input) using a set of observations based on the assumption of normal distributions. Fuzzy linear regression is the most fundamental method in the field of fuzzy modeling in which the uncertain relationship between target and explanatory variables is estimated, and it has been effectively used repeatedly in a wide variety of real-world applications. In this article, we examine the fuzzy regression model with the coefficients of Neutrosophic fuzzy numbers. For this, we first write a generalization of the measure of the Diamond distance for these numbers, and then estimate the parameters of the model, which are Neutrosophic triangular fuzzy numbers, using the least square method. We show and finally by citing an example, we express the application of the presented model.