Error checking: Compare with known answers

See also: Checking model behavior introduction

You may well know the output you should get when the parameters are set to certain values, which you can then check. Similarly, you may logically know what the change in your output should be by changing an input parameter (e.g. double parameter X and the output mean should double). This will also often apply when you've integrated an extension to your model, and can set some parameter values so your model is equivalent to the previous version. Another technique is to set some parameters to particular values (most common would be setting some probability or rate to zero) that will render a part of your model irrelevant, and then check that the model is indeed not affected by the part that should now be irrelevant.

Read on: Analyzing outputs

 

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