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[Sep. 23rd, 2005|01:57 pm]
A random question for people with science leanings:

I need a probability distribution, but its shape isn't really known. That inclines me to use a gaussian as a generic, because most things are gaussian.

However, it can't produce negative values. What would you use?

Truncate the gaussian below zero? Fold negative values back to positive? Something like a chi-square distribution that looks gaussian once the mean is far from zero?

[User Picture]From: dr_tectonic
2005-09-23 04:00 pm (UTC)
Ah! Okay, gotcha. Yeah, I think people are definitely non-Markovian in their decision process.

I'll fool around with gammas some. (Hopefully, when we do some sensitivity analysis of the model, one of the things we'll find out is that the details of the distribution of thresholds is not especially important. That'd be convenient.)
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[User Picture]From: melted_snowball
2005-09-23 04:55 pm (UTC)
There's a few decent handbooks on basic distributions that are a sensible thing to have on your shelf. I don't have any of them (I have a mathematical statistics book), but getting one of them is sensible.
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