nlcpy.random.RandomState.geometric

RandomState.geometric(self, p, size=None)

Draws samples from a geometric distribution.

Bernoulli trials are experiments with one of two outcomes: success or failure (an example of such an experiment is flipping a coin). The geometric distribution models the number of trials that must be run in order to achieve success. It is therefore supported on the positive integers, k = 1, 2, .... The probability mass function of the geometric distribution is

$f(k) = (1 - p)^{k - 1} p$

where p is the probability of success of an individual trial.

Parameters

pfloat: The probability of success of an individual trial.
sizeint or tuple of ints, optional: Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn.

Returns

outndarray: Drawn samples from the parameterized geometric distribution.

Restriction

If p is neither a scalar nor None : NotImplementedError occurs.

Examples

Draw ten thousand values from the geometric distribution, with the probability of an individual success equal to 0.35:

>>> import nlcpy as vp
>>> z = vp.random.geometric(p=0.35, size=10000)

How many trials succeeded after a single run?

>>> vp.sum(z == 1) / 10000  
array(0.3527)  # random