Linear regression remains a cornerstone of statistical analysis, offering a framework for modelling relationships between a dependent variable and one or more independent predictors. Over the past ...

Fuzzy regression models extend traditional statistical regression by integrating fuzzy set theory to better handle imprecision and uncertainty inherent in many real-world data sets. These models ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to ...

Implementing LRR from scratch is harder than using a library like scikit-learn, but it helps you customize your code, makes it easier to integrate with other systems, and gives you a complete ...

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...

In this paper, we introduce a new identification and estimation strategy for partially linear regression models with a general form of unknown heteroscedasticity, that is, Y = X'β₀ + m(Z) + U and U = ...

Watson (1955) investigated the performance of a regression analysis based on the assumption that the error covariance matrix is σ2γ when it is, in fact, σ2α. In ...