Implementation of Univariate Linear Regression AIM: To implement univariate Linear Regression to fit a straight line using least squares.

Combining these results lead to the proposed Adaptive Optimizable Gaussian Process Regression Linear Least Squares Regression (AO-GPRLLSR) Filtering pipeline. The AO-GPRLLSR method generated an ...

Understanding the linear relationship between two numerical variables is essential for effective data analysis. Pearson’s correlation coefficient (r) measures the strength and direction of an ...

The sag of conductors and ground wires is a key indicator of construction quality and operational safety for overhead transmission lines. This paper introduces a sag measurement platform combining ...

Background: To address the limitations of commonly used cross-validation methods, the linear regression method (LR) was proposed to estimate population accuracy of predictions based on the implicit ...

In conclusion, calculating a least squares regression line is a crucial method for analyzing correlations between two variables using linear regression. By understanding how to derive this ...

A comparison between this maximum-likelihood linear regression method for Poisson data and two alternative methods often used for the regression of count data—the ordinary least–square regression and ...

The least-squares growth rate is a statistical method used to estimate the average rate of growth of a variable over time by fitting a trend line through the data points using the least-squares ...