sympy.stats.NormalGamma() function in Python
Last Updated :
18 Aug, 2020
With the help of sympy.stats.NormalGamma() method, we can create a bivariate joint random variable with multivariate Normal gamma distribution.
Syntax: sympy.stats.NormalGamma(syms, mu, lamda, alpha, beta)
Parameters:
syms: the symbol, for identifying the random variable
mu: a real number, the mean of the normal distribution
lambda: a positive integer
alpha: a positive integer
beta: a positive integer
Returns: a bivariate joint random variable with multivariate Normal gamma distribution.
Example #1 :
Python3
from sympy.stats import density, NormalGamma
from sympy import symbols, pprint
y, z = symbols( 'y z' )
X = NormalGamma( 'X' , 0 , 1 , 2 , 3 )
norGammaDist = density(X)(y, z)
pprint(norGammaDist)
|
Output :
2
-y *z
------
___ 3/2 -3*z 2
9*\/ 2 *z *e *e
--------------------------
____
2*\/ pi
Example #2 :
Python3
from sympy.stats import density, NormalGamma
from sympy import symbols, pprint
y, z = symbols( 'y z' )
X = NormalGamma( 'X' , 1 / 2 , 3 , 4 , 6 )
norGammaDist = density(X)(y, z)
pprint(norGammaDist)
|
Output :
2
-3*z*(y - 1/2)
----------------
___ 7/2 -6*z 2
108*\/ 6 *z *e *e
--------------------------------------
____
\/ pi
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