Python Scipy stats.fisk()用法及代碼示例

scipy.stats.fisk()是一個Fisk連續隨機變量。它也被稱為log-logistic分布，它等於d == 1的Burr分布，並以標準格式和一些形狀參數定義以完成其規格。

代碼1：創建Fisk連續隨機變量

from scipy.stats import fisk 
  
numargs = fisk.numargs 
[a] = [0.7, ] * numargs 
rv = fisk(a) 
  
print ("RV : \n", rv)  

輸出：

RV : 
 <scipy.stats._distn_infrastructure.rv_frozen object at 0x0000018D568102B0>

代碼2：無序隨機變量和概率分布。

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

輸出：

Random Variates : 
 [7.79438195 3.97977194 3.20802248 3.02623867 9.36996936 8.54462365
 0.47436888 0.4645239  2.1188909  1.49435511]

Probability Distribution : 
 [0.00357142 0.0392706  0.07489491 0.11037659 0.1456485  0.18064439
 0.21529915 0.2495491  0.28333225 0.31658852]
 

代碼3：圖形表示。

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))

輸出：

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.        ]

代碼4：改變位置參數

import matplotlib.pyplot as plt 
import numpy as np 
  
x = np.linspace(0, 5, 100) 
  
# Varying positional arguments 
y1 = fisk.pdf(x, 1, 3) 
y2 = fisk.pdf(x, 1, 4) 
plt.plot(x, y1, "*", x, y2, "r--")

輸出：