diff --git a/HLearn-distributions.cabal b/HLearn-distributions.cabal
--- a/HLearn-distributions.cabal
+++ b/HLearn-distributions.cabal
@@ -1,5 +1,5 @@
 Name:                HLearn-distributions
-Version:             0.0.1.2
+Version:             0.0.1.3
 Synopsis:            Distributions for use with the HLearn library
 Description:         This module is used to estimate statistical distributions from data.  The focus is a clean interface inspired by algebra.
 Category:            Data Mining, Machine Learning, Statistics
@@ -63,7 +63,7 @@
         
         QuickCheck              >= 2.5.1,
         vector                  >= 0.9,
-        vector-th-unbox         == 0.1.0.1,
+        vector-th-unbox         >= 0.2,
         
         -- are these really necessary?
         MonadRandom             >= 0.1.6,
diff --git a/src/HLearn/Models/Distributions/Gaussian.lhs b/src/HLearn/Models/Distributions/Gaussian.lhs
--- a/src/HLearn/Models/Distributions/Gaussian.lhs
+++ b/src/HLearn/Models/Distributions/Gaussian.lhs
@@ -183,8 +183,13 @@
 --     [| \ (Gaussian n m1 m2 f) -> (n,m1,m2,f) |]
 --     [| \ (n,m1,m2,f) -> (Gaussian n m1 m2 f) |]
 
+-- derivingUnbox "Gaussian"
+--     [d| instance (U.Unbox a) => Unbox' (Gaussian a) (Int, a, a, Int) |]
+--     [| \ (Gaussian n m1 m2 dc) -> (n,m1,m2,dc) |]
+--     [| \ (n,m1,m2,dc) -> (Gaussian n m1 m2 dc) |]
+
 derivingUnbox "Gaussian"
-    [d| instance (U.Unbox a) => Unbox' (Gaussian a) (Int, a, a, Int) |]
+    [t| (U.Unbox a) => (Gaussian a) -> (Int, a, a, Int) |]
     [| \ (Gaussian n m1 m2 dc) -> (n,m1,m2,dc) |]
     [| \ (n,m1,m2,dc) -> (Gaussian n m1 m2 dc) |]