stdlib-js/stats-base-dists-triangul...

Triangular distribution excess kurtosis.

Python

Apache License 2.0

This project provides a function to calculate the excess kurtosis of a triangular distribution, a statistical measure of the "tailedness" of the probability distribution. It is part of the stdlib library, a comprehensive JavaScript library for numerical and scientific computing, and is intended for developers and researchers working with statistical analysis and probability distributions in JavaScript or Node.js environments.

Total donated

Undistributed

Share with your subscribers:

Recipients

How the donated funds are distributed

Support the dependencies of stdlib-js/stats-base-dists-triangular-kurtosis

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

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

stdlib-js/math-base-napi-ternary

C APIs for registering a Node-API module exporting an interface for invoking a ternary numerical function.

stdlib-js/utils-library-manifest

Load a manifest for compiling source files.

stdlib-js/array-float64

Float64Array.

stdlib-js/constants-float64-eps

Difference between one and the smallest value greater than one that can be represented as a double-precision floating-point number.

stdlib-js/math-base-special-abs

Compute the absolute value of a double-precision floating-point number.

stdlib-js/random-base-randu

Uniformly distributed pseudorandom numbers between 0 and 1.

stdlib-js/string-format

Insert supplied variable values into a format string.

stdlib-js/utils-try-require

Wrap `require` in a try/catch block.

tape-testing/tape

tap-producing test harness for node and browsers

gotwarlost/istanbul

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 cases including unit tests, server side functional tests and browser tests. Built for scale