Python Scipy stats.burr()用法及代码示例

scipy.stats.burr()是毛刺连续随机变量，使用标准格式和一些形状参数定义该毛刺连续随机变量以完成其规格。

代码1：创建毛刺连续随机变量

# importing scipy 
from scipy.stats import burr 
  
numargs = burr.numargs 
[a, b] = [0.6, ] * numargs 
rv = burr(a, b) 
  
print ("RV : \n", rv)

输出：

RV : 
 <scipy.stats._distn_infrastructure.rv_frozen object at 0x0000029482FCC438>

代码2：β随机变量和概率分布函数。

import numpy as np 
quantile = np.arange (0.01, 1, 0.1) 
   
# Random Variates 
R = burr.rvs(a, b, scale = 2,  size = 10) 
print ("Random Variates : \n", R) 
  
# PDF 
R = burr.pdf(quantile, a, b, loc = 0, scale = 1) 
print ("\nProbability Distribution : \n", R)

输出：

Random Variates : 
 [1.51241629e-04 3.47964171e-01 2.94154949e-02 5.10430246e-02
 1.82413279e-02 2.12564883e+00 3.51099766e-05 2.32907895e+01
 6.24723647e-04 2.79124934e-01]

Probability Distribution : 
 [6.21994723 1.01375434 0.57575653 0.40021455 0.30462819 0.24439598
 0.20298921 0.17281591 0.14988693 0.1319016 ] 

代码3：图形表示。

import numpy as np 
import matplotlib.pyplot as plt 
  
distribution = np.linspace(0, np.minimum(rv.dist.b, 5)) 
print("Distribution : \n", distribution) 
  
plot = plt.plot(distribution, rv.pdf(distribution))

输出：

Distribution : 
 [0.         0.10204082 0.20408163 0.30612245 0.40816327 0.51020408
 0.6122449  0.71428571 0.81632653 0.91836735 1.02040816 1.12244898
 1.2244898  1.32653061 1.42857143 1.53061224 1.63265306 1.73469388
 1.83673469 1.93877551 2.04081633 2.14285714 2.24489796 2.34693878
 2.44897959 2.55102041 2.65306122 2.75510204 2.85714286 2.95918367
 3.06122449 3.16326531 3.26530612 3.36734694 3.46938776 3.57142857
 3.67346939 3.7755102  3.87755102 3.97959184 4.08163265 4.18367347
 4.28571429 4.3877551  4.48979592 4.59183673 4.69387755 4.79591837
 4.89795918 5.        ]

代码4：改变位置参数

import matplotlib.pyplot as plt 
import numpy as np 
  
x = np.linspace(0, 1.0, 100) 
  
# Varying positional arguments 
y1 = burr.pdf(x, 2.75, 2.75) 
y2 = burr.pdf(x, 3.25, 3.25) 
plt.plot(x, y1, "*", x, y2, "r--")

输出：