numpy.random.RandomState.exponential¶
- RandomState.exponential(scale=1.0, size=None)¶
Exponential distribution.
Its probability density function is
f(x; \frac{1}{\beta}) = \frac{1}{\beta} \exp(-\frac{x}{\beta}),
for x > 0 and 0 elsewhere. \beta is the scale parameter, which is the inverse of the rate parameter \lambda = 1/\beta. The rate parameter is an alternative, widely used parameterization of the exponential distribution [R134].
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 [R132], or the time between page requests to Wikipedia [R133].
Parameters: scale : float
The scale parameter, \beta = 1/\lambda.
size : int or tuple of ints, optional
Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. Default is None, in which case a single value is returned.
References
[R132] (1, 2) Peyton Z. Peebles Jr., “Probability, Random Variables and Random Signal Principles”, 4th ed, 2001, p. 57. [R133] (1, 2) “Poisson Process”, Wikipedia, http://en.wikipedia.org/wiki/Poisson_process [R134] (1, 2) “Exponential Distribution, Wikipedia, http://en.wikipedia.org/wiki/Exponential_distribution