Probabilistic Principal Components Analysis. [VAR, U, LAMBDA] = ppca(X, ppca_DIM) computes the principal
％ component subspace U of dimension ppca_DIM using a centred covariance
matrix X. The variable VAR contains the off-subspace variance (which
is assumed to be spherical), while the vector LAMBDA contains the
variances of each of the principal components. This is computed
using the eigenvalue and eigenvector decomposition of X.
