[R] question about Principal Component Analysis in R?

From: Michael <comtech.usa_at_gmail.com>
Date: Mon 27 Feb 2006 - 20:00:06 EST

Hi all,

I am wondering in R, suppose I did the principal component analysis on training data set and obtain the rotation matrix, via:

> pca=prcomp(training_data, center=TRUE, scale=FALSE, retx=TRUE);

Then I want to rotate the test data set using the

> d1=scale(test_data, center=TRUE, scale=FALSE) %*% pca$rotation;
> d2=predict(pca, test_data, center=TRUE, scale=FALSE);

these two values are different

> min(d2-d1)

[1] -1.976152
> max(d2-d1)

[1] 1.535222

However, if I do these on the training data:

> d1=scale(training_data, center=TRUE, scale=FALSE) %*% pca$rotation;
> d2=predict(pca, training_data, center=TRUE, scale=FALSE);
> d3=pca$x;

Then the d1, d2, d3 are all the same...

So now I am confused... why does the test data have two different rotated matrix value?

Thanks a lot!

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