This project provides a linear congruential pseudorandom number generator (LCG) based on the Park and Miller algorithm, implementing the MINSTD algorithm for generating pseudorandom numbers. It's designed for developers needing fast, memory-efficient pseudorandom number generation in JavaScript, particularly for applications where cryptographic security is not required.
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Support the dependencies of stdlib-js/random-base-minstd
Int32Array.
Return a JSON representation of a typed array.
Test if an object has a specified property.
Test if a value is a boolean.
Test if a value is a collection.
Test if a value is an Int32Array.
Test if a value is a plain object.
Test if a value is a number having a positive integer value.
Copy values from x into y.
Maximum signed 32-bit integer.
Round a double-precision floating-point number toward negative infinity.
Common APIs shared across base pseudorandom number generators.
Insert supplied variable values into a format string.
stdlib TypeScript type declarations.
Define a non-enumerable read-only accessor.
Define a non-enumerable read-only property.
Define a non-enumerable read-write accessor.
Load a manifest for compiling source files.
Format an error message for production.
Create a zero-filled generic array.
Test if a double-precision floating-point numeric value is NaN.
Test if a finite double-precision floating-point number is a positive integer.
Object containing the user environment.
One-sample Kolmogorov-Smirnov goodness-of-fit test.
Time in seconds since the epoch.
tap-producing test harness for node and browsers
Yet another JS code coverage tool that computes statement, line, function and branch coverage with module loader hooks to transparently add coverage when running tests. Supports all JS coverage use ca
Minimal TAP output formatter.
Benchmark harness.
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