The stdlib-js/stats-base-dists-poisson-pmf repository provides a JavaScript implementation of the Poisson distribution probability mass function (PMF). It is part of the stdlib library, which aims to bring high-quality numerical and scientific computing to the web, and is designed for developers who need to perform statistical computations in JavaScript or Node.js environments.
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Double-precision floating-point positive infinity.
Test if a double-precision floating-point numeric value is NaN.
Test if a finite double-precision floating-point number is a nonnegative integer.
Natural exponential function.
Evaluate the natural logarithm of the factorial function.
Evaluate the natural logarithm of a double-precision floating-point number.
Degenerate distribution probability mass function (PMF).
Constant function.
Define a non-enumerable read-only property.
Insert array element values and the result of a callback function into a format string and print the result.
Difference between one and the smallest value greater than one that can be represented as a double-precision floating-point number.
Double-precision floating-point negative infinity.
Compute the absolute value of a double-precision floating-point number.
Create an array containing pseudorandom numbers drawn from a discrete uniform distribution.
Create an array containing pseudorandom numbers drawn from a continuous uniform distribution.
Insert supplied variable values into a format string.
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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