uently, it may be preferred
to work with the logarithms of probabilities and probability densities to
avoid underflow.

References
----------
.. [1] Probability density function, *Wikipedia*,
       https://en.wikipedia.org/wiki/Probability_density_function

Examples
--------
Instantiate a distribution with the desired parameters:

>>> import numpy as np
>>> from scipy import stats
>>> X = stats.Uniform(a=-1.0, b=1.0)

Evaluate the log-PDF at the desired argument:

>>> X.logpdf(0.5)
-0.6931471805599453
>>> np.allclose(X.logpdf(0.5), np.log(X.pdf(0.5)))
True

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