Write Python code that produces an array called epsilon of length 10000 for which plt. acorr(epsilon), the plot of correlation between values, produces a plot with a correlation above 0.25 at lags 0,1 and 2, and has a correlation below 0.05 for lags strictly larger than 2. Hand in your code and your plot.

Check the explanation

Explanation:

acorr() is function in matplotlib module in python. acorr() in full meaning is Auto-Correlation function(). and it it generally used to find  out   Auto-Correlation of array of x element.

matplotlib.pyplot.acorr()

# Implementation acorr()  

import matplotlib.pyplot as plt

import numpy as np

epsilon= np.random.randn(1000)

plt.title("Autocorrelation")

plt.acorr(epsilon, usevlines = True,  

    normed = True, maxlags =2,  

    lw = 3)

plt.grid(True)

plt.show()

also i have created the exmaple for both Auto as well as cross correlation as below

import matplotlib.pyplot as plt

import numpy as np

np.random.seed(10**3)

x, y = np.random.randn(2, 1000)

fig, [ax1, ax2] = plt.subplots(2, 1, sharex=True)

ax2.acorr(x, usevlines=True, normed=True, maxlags=50, lw=2)

ax2.grid(True)

ax1.xcorr(x, y, usevlines=True, maxlags=50, normed=True, lw=2)

ax1.grid(True)

plt.show()

this seems to be in the wrong category. but i'll take some free points my dude

posting this in wrong category will result in people seeing it who won't know the answer.