Python Scipy stats.f()用法及代码示例

scipy.stats.f()是F连续随机变量，使用标准格式和一些形状参数定义以完成其规格。

代码1：创建F个连续随机变量

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

输出：

RV : 
 <scipy.stats._distn_infrastructure.rv_frozen object at 0x0000018D566864A8>

代码2：指数F随机变量和概率分布。

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

输出：

Random Variates : 
 [2.77609532e+00 2.55454726e-04 7.77303742e+01 2.61642158e+02
 3.39772973e-01 8.63437666e+02 3.24316832e+02 5.88915362e+06
 1.27105242e+03 7.30691909e-01]

Probability Distribution : 
 [0.00800042 0.06746857 0.10587056 0.13291306 0.15295841 0.16837285
 0.18056559 0.19043041 0.19856155 0.2053691 ]
 

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, 3)) 
print("Distribution : \n", distribution) 
  
plot = plt.plot(distribution, rv.pdf(distribution))

输出：

Distribution : 
 [0.         0.06122449 0.12244898 0.18367347 0.24489796 0.30612245
 0.36734694 0.42857143 0.48979592 0.55102041 0.6122449  0.67346939
 0.73469388 0.79591837 0.85714286 0.91836735 0.97959184 1.04081633
 1.10204082 1.16326531 1.2244898  1.28571429 1.34693878 1.40816327
 1.46938776 1.53061224 1.59183673 1.65306122 1.71428571 1.7755102
 1.83673469 1.89795918 1.95918367 2.02040816 2.08163265 2.14285714
 2.20408163 2.26530612 2.32653061 2.3877551  2.44897959 2.51020408
 2.57142857 2.63265306 2.69387755 2.75510204 2.81632653 2.87755102
 2.93877551 3.        ]

代码4：改变位置参数

import matplotlib.pyplot as plt 
import numpy as np 
  
x = np.linspace(0, 5, 100) 
  
# Varying positional arguments 
y1 = f  .pdf(x, 2, 6) 
y2 = f  .pdf(x, 1, 4) 
plt.plot(x, y1, "*", x, y2, "r--")

输出：