Least Squares Curve Fitting Using PolyFit Function

Resource Overview

Function Specification // Function Name: PolyFit // Function Purpose: Implements least squares algorithm for polynomial curve fitting with coefficient calculation

Detailed Documentation

In the code implementation, we utilize the PolyFit function to perform least squares curve fitting. This function operates by fitting a set of data points to a polynomial curve, enabling better understanding and analysis of data trends. The implementation employs the least squares method to compute polynomial coefficients - a widely-used fitting technique that minimizes the sum of squared residuals between observed data and fitted values. The PolyFit function typically accepts input parameters including data point arrays (x-coordinates and y-coordinates) and the desired polynomial degree. Internally, it constructs a Vandermonde matrix from the x-values and solves the normal equations using matrix operations to determine optimal coefficients. This curve fitting approach provides a mathematical foundation for trend analysis and serves as a crucial preprocessing step for advanced data analytics workflows.