I have a set of ODE's which have three parameters k1, k2 and k3. I am solving the ode and trying to fit the result to experimental data by calculating the least squares. I want to plot a contour plot with the three parameters and the least squares value for each combination of the parameters. How can this be done in Matlab? Or is there any other way to do it.
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Do any of the examples [here](https://stackoverflow.com/q/16868074/8239061) help? – SecretAgentMan Apr 15 '19 at 11:43
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If you have 3 input variables `k1`,`k2`,`k3`, and associated output variable least sum of squared error, `SSE`, then you have 4 variables to visualize. What kind of output are you wanting (other than to use contours)? Can you draw what you're trying to achieve? If you can [edit] your question to include what you're hoping for, or link to something that illustrates it, you'll get better assistance. – SecretAgentMan Apr 15 '19 at 19:57
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I want to plot the least squares value against each set of values of k1, k2 and k3. something like a 3D contour. – Sriram Krishnamurthy Jun 10 '19 at 03:10
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Thankyou @SecretAgentMan . I checked out the link. That is a 3D plot for two variable and the corresponding function value. Can I have something similar to that except I have three variables. Can I use some visualization technique to address this? – Sriram Krishnamurthy Jun 10 '19 at 03:12
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I think a [Minimal, Reproducible Example](https://stackoverflow.com/help/minimal-reproducible-example) would help here. FYI, I've been reading up on this [here](https://towardsdatascience.com/the-art-of-effective-visualization-of-multi-dimensional-data-6c7202990c57) and [here](https://www.mathworks.com/help/matlab/visualize/visualizing-four-dimensional-data.html) and [here](https://stats.stackexchange.com/q/123767/177387). – SecretAgentMan Jun 11 '19 at 14:33
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You're welcome. That's the best we can probably do without a small [example](https://stackoverflow.com/help/minimal-reproducible-example) and a description or picture of your desired output. – SecretAgentMan Jul 02 '19 at 13:36