This is the S3 specialization of the function stats::prcomp() for QTS
samples.
# S3 method for qts_sample
prcomp(x, M = 5, fit = FALSE, ...)An object of class prcomp_qts which is a list with the following
components:
x: An object of class qts_sample as provided by the user, possibly
resampled;
tpca: An object of class MFPCAfit as produced by the function
MFPCA::MFPCA(),
var_props: A numeric vector storing the percentage of variance explained
by each PC,
total_variance: A numeric value storing the total variance of the sample,
mean_qts: An object of class qts containing the mean QTS (used for
centering the QTS sample before projecting it to the tangent space),
principal_qts: A list of qtss containing the required principal
components.
An object of class qts_sample.
An integer value specifying the number of principal component to
compute. Defaults to 5L.
A boolean specifying whether the resulting prcomp_qts object
should store a reconstruction of the sample from the retained PCs. Defaults
to FALSE.
Arguments passed to or from other methods.
The mean_qts component of the resulting object is the QTS used for
centering. It it part of the prcomp_qts object because it is needed to
reconstruct the sample from the retained PCs. The prcomp_qts object also
contains the total variance of the sample and the percentage of variance
explained by each PC.
res_pca <- prcomp(vespa64$igp[1:16])
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