With the help of sympy.stats.GeneralizedMultivariateLogGamma() method, we can get the continuous joint random variable which represents the Generalized Multivariate Log Gamma distribution.
Syntax :
GeneralizedMultivariateLogGamma(syms, delta, v, lamda, mu)
Parameters :
1) Syms – list of symbols
2) Delta – a constant in range [0, 1]
3) V – positive real number
4) Lambda – a list of positive reals
5) mu – a list of positive real numbers.
Return : Return the continuous joint random variable.
Example #1 :
In this example we can see that by using sympy.stats.GeneralizedMultivariateLogGamma() method, we are able to get the continuous joint random variable representing Generalized Multivariate Log Gamma distribution by using this method.
# Import sympy and GeneralizedMultivariateLogGamma from sympy.stats import density
from sympy.stats.joint_rv_types import GeneralizedMultivariateLogGamma
from sympy.stats.joint_rv import marginal_distribution
from sympy import symbols, S
v = 1
l, mu = [1, 1, 1], [1, 1, 1]
d = S.Half
y = symbols('y_1:4', positive = True)
# Using sympy.stats.GeneralizedMultivariateLogGamma() method Gd = GeneralizedMultivariateLogGamma('G', d, v, l, mu)
gfg = density(Gd)(y[0], y[1], y[2])
pprint(gfg) |
Output :
oo
_____
\ `
\ y_1 y_2 y_3
\ -n (n + 1)*(y_1 + y_2 + y_3) - e - e - e
\ 2 *e
/ ---------------------------------------------------
/ 3
/ Gamma (n + 1)
/____,
n = 0
----------------------------------------------------------
2
Example #2 :
# Import sympy and GeneralizedMultivariateLogGamma from sympy.stats import density
from sympy.stats.joint_rv_types import GeneralizedMultivariateLogGamma
from sympy.stats.joint_rv import marginal_distribution
from sympy import symbols, S
v = 1
l, mu = [1, 2, 3], [2, 5, 1]
d = S.One
y = symbols('y_1:4', positive = True)
# Using sympy.stats.GeneralizedMultivariateLogGamma() method Gd = GeneralizedMultivariateLogGamma('G', d, v, l, mu)
gfg = density(Gd)(y[0], y[1], y[2])
pprint(gfg) |
Output :
oo
______
\ `
\ 5*y_2 y_3
\ 2*y_1 e e
\ (n + 1)*(2*y_1 + 5*y_2 + y_3) - e - ------ - ----
\ n -n - 1 2 3
/ 10*0 *6 *e
/ ---------------------------------------------------------------------
/ 3
/ Gamma (n + 1)
/_____,
n = 0