On the Correlation between Random Variables and their Principal Components

Zenon Gniazdowski
10/9/2023
cs.LGmath.ST

No confident code implementation found for this paper. 2 possible matches can be shown below.

Abstract

The article attempts to find an algebraic formula describing the correlation coefficients between random variables and the principal components representing them. As a result of the analysis, starting from selected statistics relating to individual random variables, the equivalents of these statistics relating to a set of random variables were presented in the language of linear algebra, using the concepts of vector and matrix. This made it possible, in subsequent steps, to derive the expected formula. The formula found is identical to the formula used in Factor Analysis to calculate factor loadings. The discussion showed that it is possible to apply this formula to optimize the number of principal components in Principal Component Analysis, as well as to optimize the number of factors in Factor Analysis.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 2 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{gniazdowski2023correlation,
  title  = {On the Correlation between Random Variables and their Principal Components},
  author = {Zenon Gniazdowski},
  year   = {2023},
  eprint = {2310.06139},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.06139v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2310.06139.svg)](https://codeofpaper.com/paper/2310.06139)

Discussion