Curve fitting non-linear multi-variable functions
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I am a bit lost on the concept here, and not sure if this functionality is available in the curve fitting toolbox or machine learning toolbox. I have data from experiments (f(x)) that vary as a function of x. These have been collected by varying a parameter 13 times. I have fitted a non-linear curve (power function) to each of these experiments, and are labelled f(1) to f(13) on the image. Each of these curves share the same independent variable (x), and I am trying to fit the trend of all of these curves into a single function to show how they vary as a function of another parameter (experimental parameter). This creates a multivariable composite function g(f(x),x). Is there any way for me to use an optimization technique in order to fit all of these functions into a single function that show the trend of the curves as I go from 1 to 13? I am quite lost here.
Thank you for any assistance!
Jyotsna Talluri on 16 Jan 2020
You can use the regress function from the statitics and Machine learning toolbox to perform multple linear regression so that obtained plot will be 3D graph with z as a function of x and y
Refer to the below link