PLS_Toolbox Documentation: estimatefactors | < ellps | evolvfa > |
estimatefactors
Purpose
Estimate number of significant factors in multivariate data.
Synopsis
S = estimatefactors (x,options)
Description
Given a bilinear dataset, ESTIMATEFACTORS estimates the number of significant factors required to describe the data. The algorithm uses PCA bootstrapping (resampling) of the data. The PCA loadings determined for each resampling are compared for changes. Principal components which change significantly from one resampling to the next are probably due mostly to noise rather than signal.
The output is an estimate of the signal to noize ratio for each principal component. Ratios of 2 or below are dominated by noise, above 3 are OK, and between 2 and 3 are a jugement call. The number of factors needed to describe the data is the number of eigenvectors with signal to noise ratios greater than about 2.
This function is based on an algorithm developed and Copyrighted 1997 by Ronald C. Henry, Eun Sug Park, and Clifford H. Spiegelman and used by permission of the authors. For reference see:
* Henry, R.C., Park, E.S., & Spiegelman, C.H. (1999). Comparing A New Algorithm With The Classic Methods For Estimating The Number Of Factors. Chemometrics and Intelligent Laboratory Systems, 48(1), 91-97.
* Park, E.S., Henry, R.C., & Spiegelman C.H. (2000). Estimating The Number Of Factors To Include In A Height Dimensional Multivaraite Bilinear Model. Communications in Statistics-Theory and Methods, 29(3), 723-746.
Options
The default options can be retreived using: options = estimatefactors('options');.
See Also
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