prcomp.qts_sample | R Documentation |
This is the S3
specialization of the function stats::prcomp()
for QTS
samples.
## S3 method for class 'qts_sample'
prcomp(x, M = 5, fit = FALSE, ...)
x |
An object of class qts_sample. |
M |
An integer value specifying the number of principal component to
compute. Defaults to |
fit |
A boolean specifying whether the resulting |
... |
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.
An object of class prcomp_qts
which is a list with the following
components:
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.
res_pca <- prcomp(vespa64$igp[1:16])
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