Cov cv: Difference between revisions
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imported>Donal (Created page with '===Purpose=== Estimation of a regularized inverse covariance matrix. For (x) M by N, COV_CV estimates a regularized inverse of x'*x/(M-1). If [V,S] = svd(x'*x/(M-1)), and S = …') |
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====Optional Inputs==== | ====Optional Inputs==== | ||
* '''options''' = structure array with the following fields | * '''options''' = structure array with the following fields discussed below. | ||
====Outputs==== | ====Outputs==== |
Revision as of 16:28, 2 September 2010
Purpose
Estimation of a regularized inverse covariance matrix.
For (x) M by N, COV_CV estimates a regularized inverse of x'*x/(M-1).
If [V,S] = svd(x'*x/(M-1)), and S = diag(S); then the regularized inverse takes the form V*diag(1./(S+alpha))*V'.
The 1 by N vector alpha is output in (results.alpha) [see options.algorithm].
Synopsis
- [ccov,results] = cov_cv(x,options);
Inputs
- x = X-block class "double" or "dataset".
Optional Inputs
- options = structure array with the following fields discussed below.
Outputs
- ccov = the regularized (inverse and/or sqrt) covariance.
- results = a structure array with the following fields
Example
load nir_data [ccov,results] = cov_cv(spec1); axis([0 50 1e-8 1]), vline(results.ncomp), hline(results.s(1)/results.options.condmax) title(['nir_data: 30x401 ',get(get(gca,'title'),'string')],'interpreter','none'), figfont