Initialize BPCA model

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Description

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

Usage

1
BPCA_initmodel(y, components)

Arguments

y

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

components

Number of components used for estimation

Details

The function calculates the initial Eigenvectors by use of SVD from the complete rows. The data structure M is created and initial values are assigned.

Value

List containing

rows

Row number of input matrix

cols

Column number of input matrix

comps

Number of components to use

yest

(working variable) current estimate of complete data

row_miss

(Array) Indizes of rows containing missing values

row_nomiss

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

nans

Matrix of same size as input data. TRUE if input == NA, false otherwise

mean

Column wise data mean

PA

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

tau

Estimated precision of the residual error

scores

Estimated scores

Further elements are: galpha0, balpha0, alpha, gmu0, btau0, gtau0, SigW. These are working variables or constants.

Author(s)

Wolfram Stacklies

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