Statistical regression analysis is a powerful and reliable method to determine the impact of
one or several independent variable (s) on a dependent variable. It is the most widely used …

In regression analysis, the rank transform (RT) method is known to be neither dependent on
the shape of the error distribution nor sensitive to outliers. In this paper, we construct a so …

In data analysis, analyzing the relationships between the variables such as correlation
analysis and regression analysis are very important. Correlation analysis and regression …

This paper is an attempt to develop a novel linear regression model with autocorrelated
fuzzy error terms and exact predictors and fuzzy responses. The conventional Durbin …

In this work, the coefficients of the simple linear regression model between the study
variables in an intuitionistic fuzzy (IF) environment are found using an index matrix approach …

Regression Analysis is an analyzing method of regression model to explain the statistical
relationship between explanatory variable and response variables. This paper introduce …

Regression analysis is an analyzing method of regression model to explain the statistical
relationship between explanatory variable and response variables. This paper propose a …

A fuzzy least squares estimator in the multiple with fuzzy-input–fuzzy-output linear
regression model is considered. The paper provides a formula for the L 2 estimator of the …

This paper proposes a new form of the multiple regression model (mixed model) based on
adding both fuzzy and crisp input data. The least squares approach of the proposed multiple …

Linear regression models play a crucial role in capturing the linear relationships between
response and predictor variables, relying on specific assumptions. These assumptions …