This is the `S3`

specialization of the function `stats::prcomp()`

for QTS
samples.

## Usage

```
# S3 method for 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

`5L`

.- fit
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.

## Value

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.

## 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.

## Examples

```
res_pca <- prcomp(vespa64$igp[1:16])
#> ℹ The maximum number of principal component is 15.
```