Description Usage Arguments Value References Examples
View source: R/cov-estim-evc.R
Computes a PCA estimator of the covariance matrix.
1 | sigma_estim_pca(data, number_pc = NULL)
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data |
an nxp data matrix |
number_pc |
an integer, indicating the number of principal components. Default value is NULL and the number of principal components is set according to the Marcenko-Pastur edge as in \insertCitemarvcenko1967distribution;textualCovEstim. |
a list with the following entries
a pxp estimated covariance matrix.
an estimation specific tuning parameter, here the number of principal components.
johnson2002appliedCovEstim
\insertReffan2016overviewCovEstim
1 2 3 4 5 6 | data(sp200)
sp_rets <- sp200[1:100,-1]
sigma_pca2 <- sigma_estim_pca(sp_rets, number_pc=2)[[1]] # user-defined number of factors
results_pca_mp <- sigma_estim_pca(sp_rets) # number of factors, defined with MP cut-edge
sigma_pca_mp <- results_pca_mp[[1]]
number_pc <- results_pca_mp[[2]]
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