The purpose of this tutorial is to continue our exploration of multivariate statistics by conducting a simple (one explanatory variable) linear regression ... now (having used regression in Excel and ...

In this tutorial, we will look at three most popular non-linear regression models and how to solve them in R. This is a hands-on tutorial for beginners with the good conceptual idea of regression and ...

Explain the coefficients or parameters with a focus on the issue at hand. Linear regression is an essential form of statistical analysis performed in R programming with the aim of finding a ...

Abstract: When we use linear programming in possibilistic regression analysis, some coefficients tend to become crisp because of the characteristic of linear programming. On the other hand, a ...

Linear Programming: Basics, Simplex Algorithm, and Duality. Applications of Linear Programming: regression, classification and other engineering applications. Integer Linear Programming: Basics, ...

Abstract: When we use linear programming in possibilistic regression analysis, some coefficients tend to become crisp because of the characteristic of linear programming. On the other hand, a ...