Compute the covariance of two one-dimensional ndarrays provided known means and using a one-pass textbook algorithm.
JavaScript
0
0
Apache License 2.0
This project is a JavaScript library for computing the covariance of two one-dimensional ndarrays using a one-pass textbook algorithm, provided known means. It is part of stdlib, a standard library for JavaScript and Node.js focused on numerical and scientific computing. The library is designed for developers working with numerical data who need to calculate covariance efficiently and accurately.
Total donated
Undistributed
Share with your subscribers:
Recipients
How the donated funds are distributed
Support the dependencies of stdlib-js/stats-base-ndarray-covarmtk
Return the underlying data buffer of a provided ndarray.
Convert an ndarray-like object to a scalar value.
Return the size (i.e., number of elements) of a specified dimension for a provided ndarray.
Return the index offset specifying the underlying buffer index of the first iterated ndarray element.
Return the stride along a specified dimension for a provided ndarray.
Calculate the covariance of two strided arrays provided known means and using a one-pass textbook algorithm.
stdlib TypeScript type declarations.
Test if a double-precision floating-point numeric value is NaN.
Exponential function.
Base multidimensional array.
Convert a scalar value to a zero-dimensional ndarray.
Convert a scalar value to a zero-dimensional ndarray.
Convert an ndarray to a generic array.
Create an array containing pseudorandom numbers drawn from a discrete uniform distribution.
Create an array containing pseudorandom numbers drawn from a continuous uniform distribution.
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 cases including unit tests, server side functional tests and browser tests. Built for scale
Minimal TAP output formatter.
Benchmark harness.
Support the repos that depend on stdlib-js/stats-base-ndarray-covarmtk
Top contributors
stdlib-bot
6 contributions
Recent events
Kivach works on the Obyte network, and therefore you can track all donations.
No events yet