View source: R/GPSR-predict-SVD.R
GPSubspacePredSVD | R Documentation |
44ms, w/o messaging (k=20,l=12). GP subspace regression prediction, posterior from equal likelihood
GPSubspacePredSVD(thetaNew, thetaTrain, len, t = k, method = "rsvd")
thetaNew |
a target parameter point |
t |
truncation level, defaults to k; if NULL, use thin SVD. |
To get the explicit principal directions, do matrix multiplication V = stdX$u %*% Vcirc.
a list: Vcirc, principal directions as coordinates in the global basis, a c-by-t matrix (more than the mean prediction); sigma2, principal variances, a vector of length t; eps2, noise variance, a scalar.
Require (K, XtX, VbtX)
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