diff --git a/src/pg/sql/16_getis.sql b/src/pg/sql/16_getis.sql
index 23547f1..dc3a25d 100644
--- a/src/pg/sql/16_getis.sql
+++ b/src/pg/sql/16_getis.sql
@@ -6,10 +6,11 @@ CREATE OR REPLACE FUNCTION
       column_name TEXT,
       w_type TEXT DEFAULT 'knn',
       num_ngbrs INT DEFAULT 5,
+      permutations INT DEFAULT 99,
       geom_col TEXT DEFAULT 'the_geom',
       id_col TEXT DEFAULT 'cartodb_id')
-RETURNS TABLE (z_val NUMERIC, p_val NUMERIC, rowid BIGINT)
+RETURNS TABLE (z_val NUMERIC, p_val NUMERIC, p_z_sim NUMERIC, rowid BIGINT)
 AS $$
   from crankshaft.clustering import getis_ord
-  return getis_ord(subquery, column_name, w_type, num_ngbrs, geom_col, id_col)
+  return getis_ord(subquery, column_name, w_type, num_ngbrs, permutations, geom_col, id_col)
 $$ LANGUAGE plpythonu;
diff --git a/src/py/crankshaft/crankshaft/clustering/getis.py b/src/py/crankshaft/crankshaft/clustering/getis.py
index 8cbbd56..1ee425a 100644
--- a/src/py/crankshaft/crankshaft/clustering/getis.py
+++ b/src/py/crankshaft/crankshaft/clustering/getis.py
@@ -1,10 +1,7 @@
 """
-Moran's I geostatistics (global clustering & outliers presence)
+Getis-Ord's G geostatistics (hotspot/coldspot analysis)
 """
 
-# TODO: Fill in local neighbors which have null/NoneType values with the
-#       average of the their neighborhood
-
 import pysal as ps
 import plpy
 from collections import OrderedDict
@@ -15,11 +12,11 @@ import crankshaft.pysal_utils as pu
 # High level interface ---------------------------------------
 
 def getis_ord(subquery, attr,
-              w_type, num_ngbrs, geom_col, id_col):
+              w_type, num_ngbrs, permutations, geom_col, id_col):
     """
-    Getis-Ord's G
-    Implementation building neighbors with a PostGIS database and Getis-Ord's G
-     hotspot/coldspot analysis with PySAL.
+    Getis-Ord's G*
+    Implementation building neighbors with a PostGIS database and PySAL's Getis-Ord's G*
+     hotspot/coldspot module.
     Andy Eschbacher
     """
 
@@ -38,14 +35,17 @@ def getis_ord(subquery, attr,
         result = plpy.execute(query)
         # if there are no neighbors, exit
         if len(result) == 0:
-            return pu.empty_zipped_array(3)
+            return pu.empty_zipped_array(4)
     except plpy.SPIError, err:
         plpy.error('Query failed: %s' % err)
 
     attr_vals = pu.get_attributes(result)
+
+    ## build PySAL weight object
     weight = pu.get_weight(result, w_type, num_ngbrs)
 
-    # calculate LISA values
-    getis = ps.esda.getisord.G_Local(attr_vals, weight, star=True)
+    # calculate Getis-Ord's G* z- and p-values
+    getis = ps.esda.getisord.G_Local(attr_vals, weight,
+      star=True, permutations=permutations)
 
-    return zip(getis.z_sim, getis.p_sim, weight.id_order)
+    return zip(getis.z_sim, getis.p_sim, getis.p_z_sim, weight.id_order)