With the help of sympy.stats.MultivariateT() method, we can create a joint random variable with multivariate T-distribution.
Syntax: sympy.stats.MultivariateT(syms, mu, sigma, v) Parameters: syms: the symbol for identifying the random variable mu: a matrix representing the location vector sigma: The shape matrix for the distribution v: a real number Returns: a joint random variable with multivariate T-distribution.
Example #1 :
Python3
# import sympy, MultivariateT, density, Symbol from sympy.stats import density, MultivariateT
from sympy import Symbol, pprint
x = Symbol( "x" )
# using sympy.stats.MultivariateT() method X = MultivariateT( "x" , [ 1 , 1 ], [[ 1 , 0 ], [ 0 , 1 ]], 2 )
multiVar = density(X)( 1 , 2 )
pprint(multiVar) |
Output :
2 ---- 9*pi
Example #2 :
Python3
# import sympy, MultivariateT, density, Symbol from sympy.stats import density, MultivariateT
from sympy import Symbol, pprint
x = Symbol( "x" )
# using sympy.stats.MultivariateT() method X = MultivariateT( "x" , [ 1 , 1 , 1 ], [[ 1 , 0 , 1 ], [ 0 , 1 , 0 ], [ 0 , 0 , 1 ]], 1 / 2 )
multiVar = density(X)( 1 , 2 , 3 )
pprint(multiVar) |
Output :
4 ____ ___ 2*\/ 11 *\/ 2 *Gamma(7/4) ------------------------- 3/2 121*pi *Gamma(1/4)