fuzzy random variables

In this article, logistic regression models are studied in which the response variables are two (or multiple) values and the explanatory variables (predictor or independent) are ordinary variables, but the errors have a vagueness nature in addition to being random. Based on this, we formulate the proposed model and determine the estimation of the coefficients for a case with only one explanatory variable using the method of least squares. In the end, we explain the results with an example.

In this paper, we study the fuzzy random variable and its cumulative distribution function and express the combined fuzzy random variable and their cumulative distribution function. Then, we express the concept of copula and its application in the construction of jointly cumulative distribution function and the application of copula is expressed in the construction of a jointly cumulative distribution function for two fuzzy random variables. Finally, to better understand, an example is presented.