R package for performing
principal component analysis PCA
with applications to missing value imputation. Provides a single
interface to performing PCA using
SVD: a fast method which is also the standard method in R but
which is not applicable for data with missing values.
NIPALS: an iterative fast method which is applicable also to
data with missing values.
PPCA: Probabilistic PCA which is applicable also on data with
missing values. Missing value estimation is typically better than
NIPALS but also slower to compute and uses more memory. A port to R
of the
implementation by Jakob Verbeek.
BPCA: Bayesian PCA which performs very well in the presence of
missing values but is slower than PPCA. A port of the
matlab implementation by Shigeyuki Oba.