method
RandomState.
exponential
Draw samples from an exponential distribution.
Its probability density function is
System Message: WARNING/2 (f(x; \frac{1}{\beta}) = \frac{1}{\beta} \exp(-\frac{x}{\beta}), )
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for x > 0 and 0 elsewhere.
x > 0
System Message: WARNING/2 (\beta)
System Message: WARNING/2 (\lambda = 1/\beta)
The exponential distribution is a continuous analogue of the geometric distribution. It describes many common situations, such as the size of raindrops measured over many rainstorms [1], or the time between page requests to Wikipedia [2].
Note
New code should use the exponential method of a default_rng() instance instead; see random-quick-start.
default_rng()
The scale parameter,
System Message: WARNING/2 (\beta = 1/\lambda)
Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. If size is None (default), a single value is returned if scale is a scalar. Otherwise, np.array(scale).size samples are drawn.
(m, n, k)
m * n * k
None
scale
np.array(scale).size
Drawn samples from the parameterized exponential distribution.
See also
Generator.exponential
which should be used for new code.
References
Peyton Z. Peebles Jr., “Probability, Random Variables and Random Signal Principles”, 4th ed, 2001, p. 57.
Wikipedia, “Poisson process”, https://en.wikipedia.org/wiki/Poisson_process
Wikipedia, “Exponential distribution”, https://en.wikipedia.org/wiki/Exponential_distribution