MATLAB: Simbiology Sensitivity analysis on dumthe variable assigned through a repeatedAssignment Rule

sensitivity analysissensitivity simbiologySimBiology

Hello,

The title pretty much covers my question: I'm trying to use the 'Calculate sensitivities' Task in SimBiology desktop on a dummy variable whose value is enforced through a repeatedAssignment rule in my model, but I get the error:

'An input or output cannot be the left-handside variable of a repeated assignment rule'

I understand what the error is, but I'm wondering if there are any tricks/strategies around this restriction in the sensitivity calculator?

Thanks in advance!

Best Answer

One approach is to analytically differentiate the repeated assignment rule, and figure out how to calculate the desired sensitivity in terms of other sensitivities you can get from simulations. For example, if the repeated assigment rule is A = B + C, then then sensitivity of A would be the sensitivity of B plus the sensitivity of C.

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MATLAB: Performing infusion experiment in Simbiology desktop

Hi Rajeev,

whether you choose a repeated dose or a scheduled dose has rather to do with the schedule of your drug regimen. Both support bolus and infusion dosing.

For an infusion, you will need to specify an infusion rate. Please refer to this page of SimBiology's documentation: Doses

Best,

Jérémy

MATLAB: Interaction dummies

Here is a specific example of how to do it. If you need to generalize it and can't figure that out, let me know. The idea is to multiply the first column of d1 by each column of d2, then the second column of d1 by each column of d2:

d1 = dummyvar(T); d2 = dummyvar(R);
d1(:,[1 1 1 2 2 2]).*d2(:,[1 2 3 1 2 3])

Another thing to consider is the x2fx function, using something like this:

x2fx([T R],'interaction',1:2)

This requests that both T and R be treated as categorical, and that all columns for an interaction model be computed. You'll see the result has a column of ones, then dummy columns for T and R separately, then columns for the interaction. The idea is that these will be used in regression, so certain columns are omitted so that the full matrix is not overdetermined.

Best Answer

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MATLAB: Performing infusion experiment in Simbiology desktop

MATLAB: Interaction dummies

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