stdlib-js

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

Negative binomial distribution mode.

Python
2
0
Apache License 2.0

This package provides a function to calculate the mode of a negative binomial distribution, which is a discrete probability distribution that models the number of failures until a specified number of successes occur. The mode is calculated using the formula floor(p(r-1)/(1-p)) when r > 1, and 0 otherwise, where r is the number of successes and p is the success probability. It's designed for use in statistical computing and is part of the stdlib JavaScript library, making it suitable for developers working on numerical and scientific applications in Node.js or web browsers.

Total donated
Undistributed
Share with your subscribers:

Recipients

How the donated funds are distributed

Support the dependencies of stdlib-js/stats-base-dists-negative-binomial-mode

Account's avatar
Test if a double-precision floating-point numeric value is NaN.
Account's avatar
C APIs for registering a Node-API module exporting an interface for invoking a binary numerical function.
Account's avatar
Round a double-precision floating-point number toward negative infinity.
Account's avatar
Load a manifest for compiling source files.
Account's avatar
Insert array element values and the result of a callback function into a format string and print the result.
Account's avatar
Difference between one and the smallest value greater than one that can be represented as a double-precision floating-point number.
Account's avatar
Double-precision floating-point negative infinity.
Account's avatar
Double-precision floating-point positive infinity.
Account's avatar
Create an array containing pseudorandom numbers drawn from a discrete uniform distribution.
Account's avatar
Create an array containing pseudorandom numbers drawn from a continuous uniform distribution.
Account's avatar
Wrap `require` in a try/catch block.
Account's avatar
tap-producing test harness for node and browsers
Account's avatar
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
Account's avatar
Minimal TAP output formatter.
Account's avatar
Benchmark harness.

Support the repos that depend on stdlib-js/stats-base-dists-negative-binomial-mode

Top contributors

stdlib-bot's profile
stdlib-bot
65 contributions

Recent events

Kivach works on the Obyte network, and therefore you can track all donations.

No events yet