PCA

One of the types of objects in Praat. See the Principal component analysis tutorial.

An object of type PCA represents the principal components analysis of a multivariate dataset.

## Commands

Creation:

  • Principal component analysis tutorial
  • TableOfReal: To PCA

## Inside a PCA

With Inspect you will see that this type contains the same attributes as an Eigen with the following extras:

numberOfObservations
  the number of observations in the multivariate dataset that originated the PCA, usually equal to the dataset's number of rows.
labels[1..dimension]
  the label that corresponds to each dimension.
centroid
  the centroids of the originating multivariate data set.

### Links to this page

- Eigen: Draw eigenvector...
- GaussianMixture & PCA: Draw concentration ellipses...
- GaussianMixture & PCA: To Matrix (density)...
- GaussianMixture: Draw concentration ellipses...
- GaussianMixture: Draw marginal pdf...
- GaussianMixture: Split component...
- GaussianMixture: To PCA
- PCA & Configuration: To TableOfReal (reconstruct)
- PCA & Covariance: Project
- PCA & PCA: Get angle between pc1-pc2 planes
- PCA & PCA: To Procrustes...
- PCA & SSCP: Project
- PCA & TableOfReal: Get fraction variance...
- PCA & TableOfReal: To Configuration...
- PCA & TableOfReal: To TableOfReal (z-scores)...
- PCA: Get eigenvalue...
- PCA: Get eigenvector element...
- PCA: Get equality of eigenvalues...
- PCA: Get fraction variance accounted for...
- PCA: Get number of components (VAF)...