Hi Alistair,
Creating a meta-model (also known as a surrogate model) for a factorial design with 3 input parameters and 1 output can be done using various methods such as polynomial regression, kriging, or neural networks. Below, I'll provide an example script using polynomial regression in MATLAB.
MATLAB Script for Polynomial Regression
Step 1: Prepare the Data - Assuming that the data is stored in a matrix where each row represents a different combination of input parameters, and the last column is the output.
Step 2: Fit a Polynomial Regression Model - You may fit a second-order polynomial regression model using MATLAB's polyfitn function from the File Exchange.
Step 3: Evaluate the Model - You can use the fitted model to predict new outputs given new inputs.
Hope this helps.
