minor fixes

Author: jstac

source/rst/heavy_tails.rst

@@ -370,10 +370,10 @@ The figure below provides one example, using simulated data.
 
 The rank-size plots shows draws from three different distributions: folded normal, chi-squared with 1 degree of freedom and Pareto.  
 
-In each case, the largest 5\% of 1,000 draws are shown.  
-
 The Pareto sample produces a straight line, while the lines produced by the other samples are concave.  
 
+You are asked to reproduce this figure in the exercises.
+
 .. _rank_size_fig1:
 
 .. figure::
@@ -416,6 +416,8 @@ Exercise 4
 
 Replicate the rank-size plot figure :ref:`presented above <rank_size_fig1>`.
 
+For each sample that you plot, you will need to reverse sort it, from largest to smallest, in order to generate the plot.
+
 Use ``np.random.seed(13)`` to set the seed.
 
 
@@ -574,7 +576,7 @@ First we will create a function and then generate the plot
 
 .. code:: ipython3
 
-    def rank_size_data(data, c=0.95):
+    def rank_size_data(data, c=1.0):
         """
         Generate rank-size data corresponding to distribution data.
         

source/rst/kesten_processes.rst

@@ -523,8 +523,8 @@ In this setting, firm dynamics can be expressed as
 .. math::
     :label: firm_dynam_ee
 
-    s_{t+1} = e_{t+1} \mathbb 1 \{s_t < \bar s\}
-        + (a_{t+1} s_t + b_{t+1}) \mathbb 1 \{s_t \geq \bar s\}
+    s_{t+1} = e_{t+1} \mathbb{1}\{s_t < \bar s\} + 
+    (a_{t+1} s_t + b_{t+1}) \mathbb{1}\{s_t \geq \bar s\}
 
 Here