refs #92 doc updats

docs/source/cf_methods.rst

@@ -35,7 +35,7 @@ Essentially these methods will sample the PDF directly, allowing them to generat
 Bayesian model selection use Bayes theorm to calculate the probability, :math:`P` of the data :math:`D` given the model :math:`M`
 
 .. math::
-   :label: int
+   :name: eq_int
 
    P(D|M) = \int_\Omega P(D| \underline{\theta}, M)P( \underline{\theta}|M)\mathrm{d\underline{\theta}}.
 
@@ -44,7 +44,7 @@ where the :math:`\underline{\theta}` are the parameters and the integral is over
 quickBayes
 ----------
 
-The quickBayes method makes a series of assumptions to reduce :ref:`the full PDF evaluation <int>` to a single analytic equation.
+The quickBayes method makes a series of assumptions to reduce :ref:`the full PDF evaluation <eq_int>` to a single analytic equation.
 The full theory is discussed here.
 The key assumptions are:
 
@@ -71,7 +71,7 @@ where :math:`P(D | M)` is the probability of the data given the model, :math:`P(
 The probability of the data will be the same for all models, so by taking a ratio the term can be removed
 
 .. math::
-   :label: eq:odds
+   :label: odds
 
    O_{21} = \frac{P(M_2 | D)}{P(M_1 | D) = \frac{P(D | M_2)P(M_2)}{P(D | M_1)P(M_1)}