eigengap.evr: Rank selection via eigenvalue ratio maximization
In sgdGMF: Estimation of Generalized Matrix Factorization Models via Stochastic Gradient Descent
eigengap.evr R Documentation
Rank selection via eigenvalue ratio maximization
Description
Select the number of significant principal components of a matrix via the
eigenvalue ratio (EVR) maximization method
Usage
eigengap.evr(covmat, maxcomp = 50, thr = 0.95)
Arguments
covmat
matrix to be decomposed
maxcomp
maximum number of eigenvalues to compute
References
Ahn, S.C., Horenstein, A.R. (2013).
Eigenvalue ratio test for the number of factors.
Econometrica, 81, 1203-1227
sgdGMF documentation built on June 8, 2025, 12:05 p.m.
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| eigengap.evr | R Documentation |
Rank selection via eigenvalue ratio maximization
Description
Select the number of significant principal components of a matrix via the eigenvalue ratio (EVR) maximization method
Usage
eigengap.evr(covmat, maxcomp = 50, thr = 0.95)
Arguments
covmat |
matrix to be decomposed |
maxcomp |
maximum number of eigenvalues to compute |
References
Ahn, S.C., Horenstein, A.R. (2013). Eigenvalue ratio test for the number of factors. Econometrica, 81, 1203-1227
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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