Minor update to mixture docs.

[ericmjl]

Just wanted to make it super clear to a user that they only have to pass in sd or tau but not both.

[ColCarroll]

I like this – there are also a few other distributions that are parameterized similarly: Normal, LogNormal, ChiSquared, HalfNormal, StudentT, HalfStudentT, AR, and GaussianRandomWalk, at least (grepping for get_tau_sd), so I might give this a day for anyone else to comment before merging in case there are strong feelings on the wording (I don't know any convention for documenting such either/or variables), and then open an issue to make the same change on those.

[ericmjl]

@fonnesbeck if this is okay for wording, I will work on PRs for the other distributions. Please let me know if you prefer an, ahem, alternative parameterization of words. 😄

[fonnesbeck]

What about blending it with the docstring, such as:

sd : array of floats
        the component standard deviations (only required if tau is not specified)
tau : array of floats
        the component precision (only required if sd is not specified)

To make it more concrete, an Example section could be added to each, along the lines of what is in some other classes:

Examples
--------
with pm.Model():
    x = pm.Normal('x', mu=0, sd=10)