diff --git a/requirements.txt b/requirements.txt
index 1c12bab28021d3dd10594cea6cb59de041bd0684..28900c3b2c3fd7621a4492e6c038b19a08d33393 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -11,4 +11,5 @@ h5py
 pandas
 tables
 future
+paramiko
 
diff --git a/wetb/wind/shear.py b/wetb/wind/shear.py
index 3d03110aff5b304807cd546c52e47153b73ffc80..4916a86ce087f06f6b0c892a36fb4b799496ad17 100644
--- a/wetb/wind/shear.py
+++ b/wetb/wind/shear.py
@@ -51,7 +51,7 @@ def fit_power_shear(z_u_lst):
 
     Parameters
     ----------
-    z_u_lst : [(z_ref, u_z_ref), (z1, u_z1),...]
+    z_u_lst : [(z_ref, u_z_ref), (z1, u_z1)]
         - z_ref: Reference height\n
         - u_z_ref: Wind speeds or mean wind speed at z_ref
         - z1: another height
@@ -73,7 +73,7 @@ def fit_power_shear(z_u_lst):
     return alpha
 
 def fit_power_shear_ref(z_u_lst, z_ref):
-    """Estimate power shear parameter, alpha, from two or morea specific reference height using polynomial fit.
+    """Estimate power shear parameter, alpha, from two or more specific reference heights using polynomial fit.
 
     Parameters
     ----------
@@ -99,7 +99,8 @@ def fit_power_shear_ref(z_u_lst, z_ref):
     """
     def shear_error(x, z_u_lst, z_ref):
         alpha, u_ref = x
-        return np.sum([(np.mean(u) - u_ref * (z / z_ref) ** alpha) ** 2 for z, u in z_u_lst])
+        return np.sum([(u - u_ref * (z / z_ref) ** alpha) ** 2 for z, u in z_u_lst])
+    z_u_lst = [(z, np.mean(u)) for z, u in z_u_lst]
     return fmin(shear_error, (.1, 10), (z_u_lst, z_ref), disp=False)