MATLAB Code Implementation for Numerical Computing
- Login to Download
- 1 Credits
Resource Overview
Detailed Documentation
In the field of numerical computing, MATLAB serves as a powerful tool for solving various mathematical problems, including differential equations, integration, interpolation, and curve fitting. Regression analysis and multiple linear regression are widely used data analysis techniques in MATLAB, enabling the construction of mathematical models for trend prediction. Key implementations involve using functions like regress() for linear regression modeling and polyfit() for polynomial fitting, with algorithms typically based on least-squares optimization. MATLAB's Statistical Toolbox further simplifies data analysis and statistical modeling through specialized functions such as fitlm() for linear model fitting and anova() for variance analysis, providing efficient workflows for hypothesis testing and parameter estimation.
- Login to Download
- 1 Credits