# ppca

## Purpose

Probabilistic Principal Components Analysis

## Synopsis

    [var, U, lambda] = pca(x, ppca_dim)

## Description

`[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`.

## See Also

`eigdec`, `pca`

Pages: Index

Copyright (c) Ian T Nabney (1996-9)