Python Scipy stats.gamma()用法及代碼示例

scipy.stats.gamma()是伽瑪連續隨機變量，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。
-> a :形狀參數
-> 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:伽瑪連續隨機變量

代碼1：創建伽瑪連續隨機變量

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

輸出：

RV:
 <scipy.stats._distn_infrastructure.rv_frozen object at 0x0000018D57997F60>

代碼2：廣義伽瑪隨機變量。

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

輸出：

Random Variates:
 [0.01601209 0.05164555 1.22072489 0.53476245 0.11529018 0.16966403
 0.59198231 0.71995529 0.86063603 3.81492177]

Probability Distribution:
 [0.00710916 0.07919869 0.15097014 0.21974949 0.28337498 0.34020629
 0.38910556 0.42939763 0.46081639 0.48344302]

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 = gamma.pdf(x, a, 1, 3) 
y2 = gamma.pdf(x, a, 1, 4) 
plt.plot(x, y1, "*", x, y2, "r--")

輸出：