使用python实现画AR模型时序图

import numpy as npimport matplotlib.pyplot as plt"""AR(1)的时序图：x[t]=a*x[t-1]+e"""num = 2000e = np.random.rand(num)x = np.empty(num) """平稳AR(1)"""a = -0.5x[0] = 2for 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 = -1.01x[0] = 2for 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 = -0.2b = 0.7x[0] = 2for 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 = -0.3b = 0.8x[0] = 2for 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 = -0.2b = 0.8x[0] = 2for 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()