On Sun, Nov 30, 2008 at 9:39 PM, Paul Butler <[EMAIL PROTECTED]> wrote:
> I've been experimenting with probability and found that in Sage, a
> probability space is also a random variable by inheritance. This may be
> useful. Without it, creating a random variable requires two classes: a
> probability space and a random variable on that probability space.
>
> Unfortunately, the random variable doesn't work like I expected. For
> example:
>
> sage: ps = DiscreteProbabilitySpace([1,2,3],{1:1/3,2:1/3,3:1/3})
> sage: ps.expectation()
> 0.333333333333333
>
> (I expected 2.00000000000000)
>
> I've prepared a patch that gives me the value I'd expect, but I'd like to
> make sure this is the proper behavior.
>
> -- Paul
>
Response from David Kohel:
Dear William, Paul,
Indeed, the function definition should be:
def expectation(self):
r"""
The expectation of the discrete random variable, namely
$\sum_{x \in S} p(x) X[x]$,
where $X$ = self and $S$ is the probability space of $X$.
"""
E = 0
Omega = self.probability_space()
for x in self._function.keys():
E += Omega(x) * x
return E
rather than:
def expectation(self):
r"""
The expectation of the discrete random variable, namely
$\sum_{x \in S} p(x) X[x]$,
where $X$ = self and $S$ is the probability space of $X$.
"""
E = 0
Omega = self.probability_space()
for x in self._function.keys():
E += Omega(x) * self(x)
return E
Cheers,
David
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