use Lognormal.from_mean_std in RiskyAsset forward simulation

HARK/ConsumptionSaving/ConsRiskyAssetModel.py

@@ -184,13 +184,9 @@ def get_Risky(self):
         else:
             RiskyAvg = self.RiskyAvg
             RiskyStd = self.RiskyStd
-        RiskyAvgSqrd = RiskyAvg ** 2
-        RiskyVar = RiskyStd ** 2
 
-        mu = np.log(RiskyAvg / (np.sqrt(1.0 + RiskyVar / RiskyAvgSqrd)))
-        sigma = np.sqrt(np.log(1.0 + RiskyVar / RiskyAvgSqrd))
-        self.shocks["Risky"] = Lognormal(
-            mu, sigma, seed=self.RNG.randint(0, 2 ** 31 - 1)
+        self.shocks["Risky"] = Lognormal.from_mean_std(
+            self.RiskyAvg, self.RiskyStd, seed=self.RNG.randint(0, 2 ** 31 - 1)
         ).draw(1)
 
     def get_Adjust(self):

HARK/distribution.py

@@ -181,11 +181,11 @@ class Lognormal(Distribution):
     Parameters
     ----------
     mu : float or [float]
-        One or more means.  Number of elements T in mu determines number
-        of rows of output.
+        One or more means of underlying normal distribution.
+        Number of elements T in mu determines number of rows of output.
     sigma : float or [float]
-        One or more standard deviations. Number of elements T in sigma
-        determines number of rows of output.
+        One or more standard deviations of underlying normal distribution.
+        Number of elements T in sigma determines number of rows of output.
     seed : int
         Seed for random number generator.
     """