Answers are grounded in this paper and cite their sources.
A common problem for both principal component analysis and image component analysis is determining how many components to retain. A number of solutions have been proposed, none of which is totally satisfactory. An alternative solution which employs a matrix of partial correlations is considered. No components are extracted after the average squared partial correlation reaches a minimum. This approach gives an exact stopping point, has a direct operational interpretation, and can be applied to any type of component analysis. The method is most appropriate when component analysis is employed as an alternative to, or a first-stage solution for, factor analysis.
No takes yet. Share an insight, caveat, or question.
Wayne F. Velicer (1976) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: