stdlib-js/random-array-geometric

Create an array containing pseudorandom numbers drawn from a geometric distribution.

JavaScript

Apache License 2.0

This package is part of the stdlib library, a standard library for JavaScript and Node.js focused on numerical and scientific computing. It provides a function to generate arrays of pseudorandom numbers following a geometric distribution, which is useful for simulations and statistical modeling. The package is designed for developers working on numerical and scientific applications in JavaScript, particularly those who need reliable random number generation for geometric distributions.

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Support the dependencies of stdlib-js/random-array-geometric

stdlib-js/array-defaults

Default array settings.

stdlib-js/array-dtypes

List of array data types.

stdlib-js/random-array-tools-unary-factory

Create a factory function for generating pseudorandom values drawn from a unary PRNG.

stdlib-js/random-base-geometric

Geometric distributed pseudorandom numbers.

stdlib-js/types

stdlib TypeScript type declarations.

stdlib-js/utils-define-nonenumerable-read-only-property

Define a non-enumerable read-only property.

stdlib-js/array-float32

Float32Array.

stdlib-js/array-float64

Float64Array.

stdlib-js/array-nans

Create an array filled with NaNs and having a specified length.

stdlib-js/array-uint32

Uint32Array.

stdlib-js/array-zeros

Create a zero-filled array having a specified length.

stdlib-js/assert-is-uint32array

Test if a value is a Uint32Array.

stdlib-js/console-log-each

Insert array element values into a format string and print the result.

stdlib-js/constants-uint32-max

Maximum unsigned 32-bit integer.

stdlib-js/math-base-assert-is-nan

Test if a double-precision floating-point numeric value is NaN.

stdlib-js/math-base-assert-is-nanf

Test if a single-precision floating-point numeric value is NaN.

stdlib-js/math-base-special-pow

Exponential function.

stdlib-js/random-base-minstd

A linear congruential pseudorandom number generator (LCG) based on Park and Miller.

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