The NumPy random.noncentral_chisquare() method returns samples from a noncentral chisquare distribution.
noncentral chi-square distribution
Example:
Python3
import matplotlib.pyplot as plt
import numpy as np
gfg = np.random.noncentral_chisquare(1.21, 9.89, 1000)
count, bins, ignored = plt.hist(gfg, 30, density = True)
plt.show() |
Output :
Syntax
Syntax: numpy.random.noncentral_chisquare(df, nonc, size=None)
Parameters
- df: Degrees of freedom, must be > 0
- nonc: Non-centrality, must be non-negative
- size: Output shape.
Return: Return the random samples as NumPy array.
How to Generate Samples from Noncentral chi-Square Distribution
To generate random samples from a noncentral chi-square distribution we use random.noncentral_chisquare() method of the NumPy library.
Let us understand it better with an example:
Example
Python3
# import numpy import numpy as np
import matplotlib.pyplot as plt
# Using noncentral_chisquare() method gfg = np.random.noncentral_chisquare(14.05, 3.24, 3000)
count, bins, ignored = plt.hist(gfg, 14, density = True)
plt.show() |
Output