numpy.random.chisquare(df, size=None)
Draw samples from a chi-square distribution.
When df
independent random variables, each with standard normal distributions (mean 0, variance 1), are squared and summed, the resulting distribution is chi-square (see Notes). This distribution is often used in hypothesis testing.
Parameters: |
df : float or array_like of floats Number of degrees of freedom, should be > 0. size : int or tuple of ints, optional Output shape. If the given shape is, e.g., |
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Returns: |
out : ndarray or scalar Drawn samples from the parameterized chi-square distribution. |
Raises: |
ValueError When |
The variable obtained by summing the squares of df
independent, standard normally distributed random variables:
is chi-square distributed, denoted
The probability density function of the chi-squared distribution is
where is the gamma function,
[R427427] | NIST “Engineering Statistics Handbook” http://www.itl.nist.gov/div898/handbook/eda/section3/eda3666.htm |
>>> np.random.chisquare(2,4) array([ 1.89920014, 9.00867716, 3.13710533, 5.62318272])
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https://docs.scipy.org/doc/numpy-1.14.2/reference/generated/numpy.random.chisquare.html