diff --git a/GPy/likelihoods/noise_models/gaussian_noise.py b/GPy/likelihoods/noise_models/gaussian_noise.py
index 2ca6c373..df351cf1 100644
--- a/GPy/likelihoods/noise_models/gaussian_noise.py
+++ b/GPy/likelihoods/noise_models/gaussian_noise.py
@@ -94,7 +94,10 @@ class Gaussian(NoiseDistribution):
 
     def _mean(self,gp):
         """
-        Mass (or density) function
+        Expected value of y under the Mass (or density) function p(y|f)
+
+        .. math::
+            E_{p(y|f)}[y]
         """
         return self.gp_link.transf(gp)
 
@@ -106,7 +109,10 @@ class Gaussian(NoiseDistribution):
 
     def _variance(self,gp):
         """
-        Mass (or density) function
+        Variance of y under the Mass (or density) function p(y|f)
+
+        .. math::
+            Var_{p(y|f)}[y]
         """
         return self.variance
 
diff --git a/GPy/likelihoods/noise_models/noise_distributions.py b/GPy/likelihoods/noise_models/noise_distributions.py
index 33a79ce8..c5297172 100644
--- a/GPy/likelihoods/noise_models/noise_distributions.py
+++ b/GPy/likelihoods/noise_models/noise_distributions.py
@@ -248,19 +248,27 @@ class NoiseDistribution(object):
 
     def _predictive_mean_analytical(self,mu,sigma):
         """
+        Predictive mean
+        .. math::
+            E(Y^{*}|Y) = E( E(Y^{*}|f^{*}, Y) )
+
         If available, this function computes the predictive mean analytically.
         """
         pass
 
     def _predictive_variance_analytical(self,mu,sigma):
         """
+        Predictive variance
+        .. math::
+            V(Y^{*}| Y) = E( V(Y^{*}|f^{*}, Y) ) + V( E(Y^{*}|f^{*}, Y) )
+
         If available, this function computes the predictive variance analytically.
         """
         pass
 
     def _predictive_mean_numerical(self,mu,sigma):
         """
-        Laplace approximation to the predictive mean: E(Y_star) = E( E(Y_star|f_star) )
+        Laplace approximation to the predictive mean: E(Y_star|Y) = E( E(Y_star|f_star, Y) )
 
         :param mu: cavity distribution mean
         :param sigma: cavity distribution standard deviation