In [1]:

    

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline


    

In [17]:

    

e = (np.random.rand(100) - 0.5) * 3.

x = 2.*np.cos(np.linspace(0, 10, e.shape[0]))

y = 1.3*x+e

y_ar = [0]
for e_i, x_i in zip(e, x):
    y_ar += [1.3*x_i + 0.3 * y_ar[-1] + e_i]
y_ar = np.array(y_ar[1:])

y_ma = []
e_i_minus_1 = 0
for e_i, x_i in zip(e, x):
    y_ma += [1.3*x_i+e_i+0.2*e_i_minus_1]
    e_i_minus_1 = e_i
y_ma = np.array(y_ma)
    
    
plt.plot(x)
plt.plot(y)
plt.plot(y_ar)
plt.plot(y_ma)


    

    
Out[17]:





[<matplotlib.lines.Line2D at 0x7fecb7073198>]






    

In [29]:

    

e = np.random.laplace(0, 2., 100)
y = e
y_ma = e + 0.7*np.r_[0., e[:-1]]
plt.plot(y)
plt.plot(y_ma)


    

    
Out[29]:





[<matplotlib.lines.Line2D at 0x7fecb6ddb0b8>]






    

In [25]:

    

np.arange(10)[:-1]


    

    
Out[25]:





array([0, 1, 2, 3, 4, 5, 6, 7, 8])

In [ ]: