stats-strided-dsnanmeanpn

Calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values, using a two-pass error correction algorithm with extended accumulation, and returning an extended precision result.

https://github.com/122321312/stats-strided-dsnanmeanpn

Science Score: 44.0%

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  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
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  • Scientific vocabulary similarity
    Low similarity (12.0%) to scientific vocabulary

Keywords

array average avg central-tendency float32 javascript mathematics nodejs single statistics stats stdlib strided strided-array
Last synced: 6 months ago · JSON representation ·

Repository

Calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values, using a two-pass error correction algorithm with extended accumulation, and returning an extended precision result.

Basic Info
  • Host: GitHub
  • Owner: 122321312
  • License: apache-2.0
  • Language: JavaScript
  • Default Branch: main
  • Size: 67.4 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Topics
array average avg central-tendency float32 javascript mathematics nodejs single statistics stats stdlib strided strided-array
Created 11 months ago · Last pushed 6 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation Security

README.md

Calculate Single-Precision Floating-Point Strided Array Mean with NaN Values Ignored

Welcome to the "stats-strided-dsnanmeanpn" repository! Here, you can find a reliable solution for calculating the arithmetic mean of a single-precision floating-point strided array. This implementation includes a two-pass error correction algorithm that efficiently handles NaN (Not a Number) values, providing an extended precision result.

If you are working with arrays containing NaN values and require an accurate mean calculation, this functionality will be a valuable addition to your project. This algorithm ensures precise results even in the presence of missing or invalid data points, enhancing the robustness of your statistical computations.

Features:

  • Efficient Algorithm: Utilizes a two-pass error correction algorithm for accurate mean calculation.
  • NaN Handling: Ignores NaN values to prevent skewing of the mean calculation.
  • Extended Precision Result: Returns an extended precision result for enhanced accuracy.
  • Strided Array Support: Designed to process single-precision floating-point strided arrays efficiently.

Usage

To utilize this calculation method, simply access the provided link for the latest releases:

Download and Execute

In the Releases section, you can access the necessary files to integrate this functionality into your project. Follow the installation instructions provided to start utilizing the extended precision mean calculation for your single-precision floating-point strided arrays.

Topics

This repository covers a range of topics related to arithmetic mean calculation and array operations, including: - Arithmetic Mean - Array Operations - Floating-Point Arithmetic - Central Tendency - Single-Precision Float32 - Mathematics - Statistics - Strided Arrays - Node.js - JavaScript - Typed Arrays

If you are engaged in mathematical computations, statistical analysis, or programming tasks involving array manipulation, this repository offers practical and reliable solutions to enhance your data processing capabilities.

Visit the repository to explore the code and access the latest updates and releases. Incorporate the extended precision mean calculation functionality into your projects to streamline your data analysis processes and ensure accurate statistical results.


By integrating this efficient mean calculation algorithm into your projects, you can confidently handle single-precision floating-point strided arrays with NaN values. Embrace precision and accuracy in your statistical computations with the extended precision mean calculation method provided in this repository. Visit the link to access the latest releases and enhance your data processing capabilities.

Owner

  • Login: 122321312
  • Kind: user

Citation (CITATION.cff)

cff-version: 1.2.0
title: stdlib
message: >-
  If you use this software, please cite it using the
  metadata from this file.

type: software

authors:
  - name: The Stdlib Authors
    url: https://github.com/stdlib-js/stdlib/graphs/contributors

repository-code: https://github.com/stdlib-js/stdlib
url: https://stdlib.io

abstract: |
  Standard library for JavaScript and Node.js.

keywords:
  - JavaScript
  - Node.js
  - TypeScript
  - standard library
  - scientific computing
  - numerical computing
  - statistical computing

license: Apache-2.0 AND BSL-1.0

date-released: 2016

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Dependencies

package.json npm
  • @stdlib/array-filled-by ^0.2.1 development
  • @stdlib/array-float32 ^0.2.2 development
  • @stdlib/assert-is-browser ^0.2.2 development
  • @stdlib/bench-harness ^0.2.2 development
  • @stdlib/math-base-assert-is-nan ^0.2.2 development
  • @stdlib/math-base-special-pow ^0.3.0 development
  • @stdlib/math-base-special-round ^0.3.0 development
  • @stdlib/random-base-bernoulli ^0.2.1 development
  • @stdlib/random-base-randu ^0.2.1 development
  • @stdlib/random-base-uniform ^0.2.1 development
  • istanbul ^0.4.1 development
  • proxyquire ^2.0.0 development
  • tap-min git+https://github.com/Planeshifter/tap-min.git development
  • tape git+https://github.com/kgryte/tape.git#fix/globby development
  • @stdlib/assert-is-error ^0.2.2
  • @stdlib/blas-base-shared ^0.1.0
  • @stdlib/napi-argv ^0.2.2
  • @stdlib/napi-argv-int64 ^0.2.2
  • @stdlib/napi-argv-strided-float32array ^0.2.2
  • @stdlib/napi-create-double ^0.0.2
  • @stdlib/napi-export ^0.2.2
  • @stdlib/strided-base-stride2offset ^0.1.0
  • @stdlib/utils-define-nonenumerable-read-only-property ^0.2.2
  • @stdlib/utils-library-manifest ^0.2.2
  • @stdlib/utils-try-require ^0.2.2