Standard library pseudorandom number generator iterators.
JavaScript
2
0
Apache License 2.0
This package provides a comprehensive collection of pseudorandom number generator (PRNG) iterators for generating random numbers from various probability distributions. It's designed for developers working on numerical computing, statistical simulations, or scientific applications who need reliable random number generation in JavaScript. The package includes iterators for common distributions like normal, uniform, binomial, and many others, making it useful for tasks such as Monte Carlo simulations, statistical modeling, and data analysis.
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Support the dependencies of stdlib-js/random-iter
Create an iterator for generating pseudorandom numbers drawn from an arcsine distribution.
Create an iterator for generating pseudorandom numbers drawn from a Bernoulli distribution.
Create an iterator for generating pseudorandom numbers drawn from a beta distribution.
Create an iterator for generating pseudorandom numbers drawn from a beta prime distribution.
Create an iterator for generating pseudorandom numbers drawn from a binomial distribution.
Create an iterator for generating pseudorandom numbers drawn from a standard normal distribution using the Box-Muller transform.
Create an iterator for generating pseudorandom numbers drawn from a Cauchy distribution.
Create an iterator for generating pseudorandom numbers drawn from a chi distribution.
Create an iterator for generating pseudorandom numbers drawn from a chi-square distribution.
Create an iterator for generating pseudorandom numbers drawn from a raised cosine distribution.
Create an iterator for generating pseudorandom numbers drawn from a discrete uniform distribution.
Create an iterator for generating pseudorandom numbers drawn from an Erlang distribution.
Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.
Create an iterator for generating pseudorandom numbers drawn from an F distribution.
Create an iterator for generating pseudorandom numbers drawn from a Fréchet distribution.
Create an iterator for generating pseudorandom numbers drawn from a gamma distribution.
Create an iterator for generating pseudorandom numbers drawn from a geometric distribution.
Create an iterator for generating pseudorandom numbers drawn from a Gumbel distribution.
Create an iterator for generating pseudorandom numbers drawn from a hypergeometric distribution.
Create an iterator for generating pseudorandom numbers drawn from a standard normal distribution using the Improved Ziggurat algorithm.
Create an iterator for generating pseudorandom numbers drawn from an inverse gamma distribution.
Create an iterator for generating pseudorandom numbers drawn from a Kumaraswamy's double bounded distribution.
Create an iterator for generating pseudorandom numbers drawn from a Laplace distribution.
Create an iterator for generating pseudorandom numbers drawn from a Lévy distribution.
Create an iterator for generating pseudorandom numbers drawn from a logistic distribution.
Create an iterator for generating pseudorandom numbers drawn from a lognormal distribution.
Create an iterator for a linear congruential pseudorandom number generator (LCG) based on Park and Miller.
Create an iterator for a linear congruential pseudorandom number generator (LCG) whose output is shuffled.
Create an iterator for a 32-bit Mersenne Twister pseudorandom number generator.
Create an iterator for generating pseudorandom numbers drawn from a negative binomial distribution.
Create an iterator for generating pseudorandom numbers drawn from a normal distribution.
Create an iterator for generating pseudorandom numbers drawn from a Pareto (Type I) distribution.
Create an iterator for generating pseudorandom numbers drawn from a Poisson distribution.
Create an iterator for generating pseudorandom numbers having integer values.
Create an iterator for generating pseudorandom numbers drawn from a standard normal distribution.
Create an iterator for generating uniformly distributed pseudorandom numbers between 0 and 1.
Create an iterator for generating pseudorandom numbers drawn from a Rayleigh distribution.
Create an iterator for generating pseudorandom numbers drawn from a Student's t distribution.
Create an iterator for generating pseudorandom numbers drawn from a triangular distribution.
Create an iterator for generating pseudorandom numbers drawn from a continuous uniform distribution.
Create an iterator for generating pseudorandom numbers drawn from a Weibull distribution.
Define a read-only property.
Int32Array.
Uint32Array.
Test if an object has a specified property.
Test if a value is a boolean.
Test if a value is an Int32Array.
Test if a value is a number having a nonnegative integer value.
Test if a value is a number.
Test if a value is a plain object.
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