numpy.random.RandomState.exponential

метод

RandomState.exponential(scale=1.0, size=None)

Генерирует выборки из экспоненциального распределения.

Его функция плотности вероятности равна

<img alt="f(x; \frac{1}{\beta}) = \frac{1}{\beta} \exp(-\frac{x}{\beta})," src="data:image/svg+xml;base64,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

for x > 0 и 0 в противном случае. является параметром масштаба, который является обратным параметру скорости . Параметр скорости — это альтернативная, широко используемая параметризация экспоненциального распределения [3].

Экспоненциальное распределение является непрерывным аналогом геометрического распределения. Оно описывает многие распространённые ситуации, такие как размер капель дождя, измеренный во многих ливнях [1], или время между запросами на страницы в Википедии [2].

Параметры:	scale : float or array_like of floats Параметр масштаба, . size : int or tuple of ints, optional Форма вывода. Если заданная форма, например, (m, n, k), то m * n * k образцов будут сгенерированы. Если размер равен None (по умолчанию), возвращается единственное значение, если scale – скаляр. В противном случае, np.array(scale).size образцов будут сгенерированы.
Возвращает:	out : ndarray or scalar Сгенерированные образцы из параметризованного экспоненциального распределения.

Ссылки

[1]	(1, 2) Peyton Z. Peebles Jr., “Probability, Random Variables and Random Signal Principles”, 4th ed, 2001, p. 57.

[2]	(1, 2) Википедия, «Процесс Пуассона», https://en.wikipedia.org/wiki/Poisson_process

[3]	(1, 2) Википедия, «Экспоненциальное распределение», https://en.wikipedia.org/wiki/Exponential_distribution