Comment #7 on issue 3129 by [email protected]: Drastic change to
sympy.stats: Adding concept of Probability Distributions on surface level
http://code.google.com/p/sympy/issues/detail?id=3129
The symbol helps in the current system by linking back to the concept
you're dealing with. Consider the following example
In [1]: from sympy.stats import *
In [2]: T = Normal(30, 3, symbol=Symbol('T')) # temperature is 30C with std
dev 3C.
In [3]: T_posterior = Given(T, T>29) # We know that T is greater than 29
In [4]: P(T<T_posterior)
ValueError
Whatever system you build needs to understand that T and T_posterior are
linked. There is more structure here between the random symbols than just
how they are distributed. This is an example of the sort of problem that
having internal symbols solves. It is sometimes useful to keep track of the
underlying concept that you're talking about.
You could also consider a bivariate probability space/distribution. You
need to ask for one of the variables within the space. Internal symbols
allow you to clearly specify what you want.
Of course, you could probably figure out a way around all of this that was
cleaner. There are some tricky situations that can come up. Internal
symbols was my solution for them.
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