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This project is a JavaScript library that generates pseudorandom numbers drawn from a discrete uniform distribution, which means each integer between a specified minimum and maximum has an equal probability of being selected. It's part of the stdlib standard library for numerical and scientific computing in JavaScript, and is intended for developers who need statistically sound random number generation in their applications, particularly those working in scientific computing, simulations, or statistical analysis.

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stdlib-js/array-to-json
Return a JSON representation of a typed array.
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Test if an object has a specified property.
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Test if a value is a function.
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Test if a value is a number having an integer value.
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Test if a value is NaN.
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Test if a value is a plain object.
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Maximum safe double-precision floating-point integer.
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stdlib-js/math-base-assert-is-integer
Test if a finite double-precision floating-point number is an integer.
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Test if a double-precision floating-point numeric value is NaN.
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Round a double-precision floating-point number toward negative infinity.
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stdlib-js/random-base-mt19937
A 32-bit Mersenne Twister pseudorandom number generator.
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Insert supplied variable values into a format string.
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stdlib TypeScript type declarations.
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Maximum unsigned 32-bit integer.
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Round a numeric value to the nearest integer.
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Object containing the user environment.
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A linear congruential pseudorandom number generator (LCG) based on Park and Miller.
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stdlib-js/random-base-minstd-shuffle
A linear congruential pseudorandom number generator (LCG) whose output is shuffled.
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stdlib-js/random-base-randu
Uniformly distributed pseudorandom numbers between 0 and 1.
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Perform a chi-square goodness-of-fit test.
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Time in seconds since the epoch.
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stdlib-js

stdlib-js/random-base-discrete-unif...

Discrete uniform distributed pseudorandom numbers.

JavaScript
2
0
Apache License 2.0