Publication Date:
2021
abstract:
Principal component analysis (PCA) was first defined in the form that is used nowadays by Pearson (1901). He found the best-fitting line in the least squares sense to the data points, which is known today as the first principal component. Hotelling (1933) showed that the loadings for the components are the eigenvectors of the sample covariance matrix. More details about the PCA history are provided in (Jolliffe, 2002, 1.2).
Iris type:
2.1 Contributo in volume (Capitolo o Saggio)
List of contributors:
Trendafilov, Nickolay; Gallo, Michele
Book title:
Multivariate Data Analysis on Matrix Manifolds (with Manopt)