BPCA_initmodel

numeric matrix containing missing values. Missing values
are denoted as 'NA'

components


Model initialization for Bayesian PCA. This function is NOT
inteded to be run separately!


Provides Bayesian PCA, Probabilistic PCA, Nipals PCA,
Inverse Non-Linear PCA and the conventional SVD PCA. A cluster
based method for missing value estimation is included for
comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA
on incomplete data as well as for accurate missing value
estimation. A set of methods for printing and plotting the
results is also provided. All PCA methods make use of the same
data structure (pcaRes) to provide a common interface to the
PCA results. Initiated at the Max-Planck Institute for
Molecular Plant Physiology, Golm, Germany.

Henning Redestig

pcaMethods

A collection of PCA methods

BPCA_initmodel function

Model initialization for Bayesian PCA. This function is NOT
inteded to be run separately!

Initialize BPCA model

rows

cols

comps

(working variable) current estimate of complete data

yest

(Array) Indizes of rows containing missing values

row_miss

(Array) Indices of complete rows (such with no
missing values)

row_nomiss

Matrix of same size as input data. TRUE if <code>input == NA</code>,
false otherwise

nans

mean

(d x k) Estimated principal axes (eigenvectors,
loadings) The matrix ROWS are the vectors

Estimated precision of the residual error

BPCA_initmodel: Initialize BPCA model

Description

Usage

Arguments

Value

Details