使用python实现画AR模型时序图

Rosine ·
更新时间:2024-11-10
· 526 次阅读

背景:

用python画AR模型的时序图。

结果:

代码:

import numpy as np import matplotlib.pyplot as plt """ AR(1)的时序图:x[t]=a*x[t-1]+e """ num = 2000 e = np.random.rand(num) x = np.empty(num) """ 平稳AR(1) """ a = -0.5 x[0] = 2 for i in range(1,num): x[i] = a*x[i-1]+e[i] plt.subplot(321,title = "AR({0}):x[t]={1}*x[t-1]+e".format(1,a)) plt.plot(x,"or") """ 非平稳AR(1) """ a = -1.01 x[0] = 2 for i in range(1,num): x[i] = a*x[i-1]+e[i] plt.subplot(322,title = "AR({0}):x[t]={1}*x[t-1]+e".format(1,a)) plt.plot(x,".b") """ 平稳AR(2) """ a = -0.2 b = 0.7 x[0] = 2 for i in range(2,num): x[i] = a*x[i-1]+b*x[i-2]+e[i] plt.subplot(323,title = "AR({0}):x[t]={1}*x[t-1]+{2}*x[t-2]+e".format(2,a,b)) plt.plot(x,"og") """ 非平稳AR(2) """ a = -0.3 b = 0.8 x[0] = 2 for i in range(2,num): x[i] = a*x[i-1]+b*x[i-2]+e[i] plt.subplot(324,title = "AR({0}):x[t]={1}*x[t-1]+{2}*x[t-2]+e".format(2,a,b)) plt.plot(x,".y") """ 非平稳AR(2) """ a = -0.2 b = 0.8 x[0] = 2 for i in range(2,num): x[i] = a*x[i-1]+b*x[i-2]+e[i] plt.subplot(313,title = "AR({0}):x[t]={1}*x[t-1]+{2}*x[t-2]+e".format(2,a,b)) plt.plot(x,"+",color="purple") plt.show()

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