eigengap.onatski: Rank selection via the Onatski method
In sgdGMF: Estimation of Generalized Matrix Factorization Models via Stochastic Gradient Descent
eigengap.onatski R Documentation
Rank selection via the Onatski method
Description
Select the number of significant principal components of a matrix via the
Onatski method
Usage
eigengap.onatski(covmat, maxcomp = 50, maxiter = 100)
Arguments
covmat
matrix to be decomposed
maxcomp
maximum number of eigenvalues to compute
maxiter
maximum number of iterations
References
Onatski, A. (2010).
Determining the number of factors from empirical distribution of eigenvalues.
Review of Economics and Statistics, 92(4): 1004-1016
sgdGMF documentation built on April 3, 2025, 7:37 p.m.
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.
| eigengap.onatski | R Documentation |
Rank selection via the Onatski method
Description
Select the number of significant principal components of a matrix via the Onatski method
Usage
eigengap.onatski(covmat, maxcomp = 50, maxiter = 100)
Arguments
covmat |
matrix to be decomposed |
maxcomp |
maximum number of eigenvalues to compute |
maxiter |
maximum number of iterations |
References
Onatski, A. (2010). Determining the number of factors from empirical distribution of eigenvalues. Review of Economics and Statistics, 92(4): 1004-1016
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.