exp_dist

mdtools.statistics.exp_dist(x, rate=1)

Exponential distribution.

\[f(x) = \lambda e^{-\lambda x}\]

The mean and standard deviation of an exponential distribution are given by \(1/\lambda\).

Parameters:

• x (scalar or array_like) – Array of \(x\) values for which to evaluate \(f(x)\).

• rate (scalar or array_like, optional) – The value(s) for \(\lambda\). If an array is provided, it must be broadcastable to a common shape with x.

Returns:

f (scalar or array_like) – The function values \(f(x)\) at the given \(x\) values.

See also

scipy.stats.expon

Exponential continuous random variable

Examples

>>> from scipy.stats import expon
>>> x = np.linspace(0, 4, 5)
>>> y1 = mdt.stats.exp_dist(x, rate=2)
>>> y2 = expon.pdf(x, loc=0, scale=1/2)
>>> np.allclose(y1, y2, rtol=0)
True
>>> y1
array([2.00000000e+00, 2.70670566e-01, 3.66312778e-02, 4.95750435e-03,
       6.70925256e-04])