Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 93 tok/s
Gemini 2.5 Pro 48 tok/s Pro
GPT-5 Medium 30 tok/s Pro
GPT-5 High 33 tok/s Pro
GPT-4o 128 tok/s Pro
Kimi K2 202 tok/s Pro
GPT OSS 120B 449 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

Measures of Correlation for Multiple Variables (1401.4827v6)

Published 20 Jan 2014 in math.ST and stat.TH

Abstract: Multivariate correlation analysis plays an important role in various fields such as statistics, economics, and big data analytics. In this paper, we propose a pair of measures, the unsigned correlation coefficient (UCC) and the unsigned incorrelation coefficient (UIC), to measure the strength of correlation and incorrelation (lack of correlation) among multiple variables. The absolute value of Pearson's correlation coefficient is a special case of UCC for two variables. Some important properties of UCC and UIC show that the proposed UCC and UIC are a pair of effective measures for multivariate correlation. We also take the unsigned tri-variate correlation coefficient as an example to visually display the effectiveness of the proposed UCC, and the geometrical explanation of UIC is also discussed. All the properties and the figures of UCC and UIC show that the proposed UCC and UIC are the general measures of correlation for multiple variables.

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.