update some doc

convoys/gamma.py

@@ -7,9 +7,12 @@
 
 @primitive
 def gammainc(k, x):
-    ''' Janky hack to make autograd compute gradients of gammainc.
+    ''' Lower regularized incomplete gamma function.
 
-    There are two problems with autograd.scipy.special.gammainc:
+    We rely on `scipy.special.gammainc 
+    <https://docs.scipy.org/doc/scipy/reference/generated/scipy.special.gammainc.html>`_
+    for this. However, there is a number of issues using this function
+    together with `autograd <https://github.com/HIPS/autograd>`_:
 
     1. It doesn't let you take the gradient with respect to k
     2. The gradient with respect to x is really slow

convoys/regression.py

@@ -76,9 +76,10 @@ class GeneralizedGamma(RegressionModel):
 
     :math:`F(t) = P(k, (t\\lambda)^p)`
 
-    where :math:`P(a, x) = \\gamma(a, x) / \\Gamma(a)` is the `lower regularized
-    incomplete gamma function
-    <https://docs.scipy.org/doc/scipy/reference/generated/scipy.special.gammainc.html>`_.
+    where :math:`P(a, x) = \\gamma(a, x) / \\Gamma(a)` is the lower regularized
+    incomplete gamma function. See :meth:`convoys.gamma.gammainc`.
+    :math:`\\gamma(a, x)` is the incomplete gamma function and :math:`\\Gamma(a)`
+    is the standard gamma function.
 
     The probability density function is:
 
@@ -336,9 +337,8 @@ class Gamma(GeneralizedGamma):
 
     :math:`F(t) = P(k, t\\lambda)`
 
-    where :math:`P(a, x) = \\gamma(a, x) / \\Gamma(a)` is the `lower regularized
-    incomplete gamma function
-    <https://docs.scipy.org/doc/scipy/reference/generated/scipy.special.gammainc.html>`_.
+    where :math:`P(a, x) = \\gamma(a, x) / \\Gamma(a)` is the lower regularized
+    incomplete gamma function. See :meth:`convoys.gamma.gammainc`.
 
     The probability density function is: