phil henshaw wrote: > Ok, 'find a function' assumes there is one to find, but the problem set is > running into behavior which has already had major consequences (like > starvation for 100million people because of an unexpected world food price > level shift) and the question is what 'function' would you use to not be > caught flat footed like that. The caloric requirements of a person are autocorrelated, but probably for a lot of models a constant will suffice -- a certain amount of body weight decrease, and then the probability of death goes up. As for price fluctuations, that's a matter of modeling the natural resources that go in to food, the costs and benefits to motivate farmers, the commodity markets, and so on. Certainly we can try to understand how each of these work, and then do what-if scenarios when one or more components are perturbed (or destroyed). It's still a matter of finding stories (functions) to fit observables. The availability and accuracy of those observables may be poor, and sometimes all that is possible to imagine worst and best cases, run the numbers, and see how the result changes. > Is there some general function to use in > cases where you have no function and don't even know what the problem > definition will be? > I think you do know what the problem could look like, but most details remain unspecified. If you can construct an example that has catastrophes of the kind you often talk about, and spell out all of the details of your work of fiction (that even may happen to resemble reality), such that the what-if scenarios can be reproduced in simulations, then others can study the sensitivities. If there is a `forcing structure' that will occur in many, many variant forms, then you can demonstrate that. > I actually have a very good one, but you won't like it because it means > using the models to understand what they fail to describe rather than the > usual method of using them to represent other things. Right. Model predicts something, it turns out to have some error structure and that structure suggests ways to improve the model or make a new one. Paper published. Meanwhile another guy makes a different model on the same phenomena and publishes a paper. Third person reads the two papers and has idea that accounts for problems in both. So she makes a new model!
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