shem: Split-Half Eigenvector Matching (SHEM)

In Rnest: Next Eigenvalue Sufficiency Test

Split-Half Eigenvector Matching (SHEM)

Description

shem estimates the number of principal components via Split-Half Eigenvector Matching (SHEM).

Usage

shem(data, nIts = 30)

Arguments

data	a data frame, a numeric matrix, covariance matrix or correlation matrix from which to determine the number of factors.
nIts	number of iterations.

Value

shem returns a list containing the number of components, nfactors, whether the additional step in case of zero true latent components was carried, zeroComponents, the eigenvalues and the eigenvectors of the solution.

References

Galdwin, T. E. (2023) Estimating the number of principal components via Split-Half Eigenvector Matching (SHEM). MethodsX, 11, 102286. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.mex.2023.102286")}

Examples

jd <- genr8(n = 404, R = ex_4factors_corr)
shem(jd)

Rnest documentation built on April 3, 2025, 5:31 p.m.