Python Scipy stats.halflogistic()用法及代碼示例

scipy.stats.halflogistic()是一個Half-logistic連續隨機變量，已使用標準格式和一些形狀參數定義以完成其規格。

參數：
-> q :上下尾概率
-> x :分位數
-> loc :[可選]位置參數。默認值= 0
-> scale:[可選]比例參數。默認值= 1
-> size :[int型元組，可選]形狀或隨機變量。
-> moments:[可選]由字母['mvsk']組成； “ m” =均值，“ v” =方差，“ s” = Fisher的偏度，“ k” = Fisher的峰度。 (默認=“ MV”)。

Results:Half-logistic連續隨機變量

代碼1：創建Half-logistic連續隨機變量

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

輸出：

RV:
 <scipy.stats._distn_infrastructure.rv_frozen object at 0x000001E39A2EA7B8>

代碼2：Half-logistic隨機變量和概率分布

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

輸出：

Random Variates:
 [1.51677656 4.2051329  3.00947016 5.00828865 8.23514322 0.46379571
 1.75794767 2.84948119 0.31392647 1.36186056]

Probability Distribution:
 [0.4999875  0.49849054 0.49452777 0.48817731 0.47956248 0.46884669
 0.45622704 0.44192689 0.42618788 0.40926186]

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：更改位置參數

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

輸出：