prcomp.qts_sample {squat} | R Documentation |
PCA for QTS Sample
Description
This is the S3
specialization of the function stats::prcomp()
for QTS
samples.
Usage
## S3 method for class 'qts_sample'
prcomp(x, M = 5, fit = FALSE, ...)
Arguments
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. |
Details
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.
Value
An object of class prcomp_qts
which is a list with the following
components:
-
tpca
: An object of classMFPCAfit
as produced by the functionMFPCA::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.
Examples
res_pca <- prcomp(vespa64$igp[1:16])