Python sympy.stats.NormalGamma()用法及代码示例

借助于sympy.stats.NormalGamma()方法，我们可以创建具有多元正态伽马分布的双变量联合随机变量。

用法： sympy.stats.NormalGamma(syms, mu, lamda, alpha, beta)
 
参数：
 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

返回： a bivariate joint random variable with multivariate Normal gamma distribution.

范例1：

# import sympy, NormalGamma, density, symbols 
from sympy.stats import density, NormalGamma 
from sympy import symbols, pprint 
  
y, z = symbols('y z') 
  
# using sympy.stats.NormalGamma() method 
X = NormalGamma('X', 0, 1, 2, 3) 
norGammaDist = density(X)(y, z) 
  
pprint(norGammaDist)

输出：

                      2   
                    -y *z 
                    ------
    ___  3/2  -3*z    2   
9*\/ 2 *z   *e    *e      
--------------------------
             ____         
         2*\/ pi      

范例2：

# import sympy, NormalGamma, density, symbols 
from sympy.stats import density, NormalGamma 
from sympy import symbols, pprint 
  
y, z = symbols('y z') 
  
# using sympy.stats.NormalGamma() method 
X = NormalGamma('X', 1 / 2, 3, 4, 6) 
norGammaDist = density(X)(y, z) 
  
pprint(norGammaDist)

输出：

                                    2 
                      -3*z*(y - 1/2)  
                      ----------------
      ___  7/2  -6*z         2        
108*\/ 6 *z   *e    *e                
--------------------------------------
                  ____                
                \/ pi