Generate Random Numbers From The Uniform Distribution using NumPy

NumPy random.noncentral_f() | Get Random Samples from noncentral F distribution

Last Updated : 09 Feb, 2024

The NumPy random.noncentral_f() method returns the random samples from the noncentral F distribution.

Example

Python3

import numpy as np 
import matplotlib.pyplot as plt 
gfg = np.random.noncentral_f(1.24, 21, 3, 1000) 
count, bins, ignored = plt.hist(gfg, 50, density = True) 
plt.show()

Output:

Syntax

Syntax: numpy.random.noncentral_f(dfnum, dfden, nonc, size=None)

Parameters:

dfnum: Degrees of freedom in numerator.

dfden: Degrees of freedom in denominator.

nonc: Non-centrality parameter.

size: Output shape.

Return: Return the random samples as numpy array.

How to Generate Random Samples from a noncentral F Distribution

To generate random samples from a noncentral F distribution we use the random.noncentral_f() method of NumPy library.

We have explained the method in the example below by plotting histogram using Matplot library.

Python3

# import numpy 
import numpy as np 
import matplotlib.pyplot as plt 
  
# Using noncentral_f() method 
gfg = np.random.noncentral_f(10.23, 12.13, 3, 10000) 
  
count, bins, ignored = plt.hist(gfg, 14, density = True) 
plt.show()

Output:

Generate Random Numbers From The Uniform Distribution using NumPy

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