Created
November 28, 2013 09:15
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Reconstruct a data set using PCA results from function "prcomp". A subset of PCs can be defined for truncated reconstruction.
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| #This function reconstructs a data set using a defined set of principal components. | |
| #arguments "pca" is the pca object from prcomp, "pcs" is a vector of principal components | |
| #to be used for reconstruction (default includes all pcs) | |
| prcomp.recon <- function(pca, pcs=NULL){ | |
| if(is.null(pcs)) pcs <- seq(pca$sdev) | |
| recon <- as.matrix(pca$x[,pcs]) %*% t(as.matrix(pca$rotation[,pcs])) | |
| if(pca$scale[1] != FALSE){ | |
| recon <- scale(recon , center=FALSE, scale=1/pca$scale) | |
| } | |
| if(pca$center[1] != FALSE){ | |
| recon <- scale(recon , center=-pca$center, scale=FALSE) | |
| } | |
| recon | |
| } |
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Hi, thanks for the code. When I try this with lesser components, I always get some negative values in reconstructed matrix. I guess this is happening at the re-scaling/re-centering part using initial values. Do you have a suggestion to fix or approximate this?
Thanks