Initialize BPCA model
Model initialization for Bayesian PCA. This function is NOT inteded to be run separately!
BPCA_initmodel(y, components)
y |
numeric matrix containing missing values. Missing values are denoted as 'NA' |
components |
Number of components used for estimation |
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.
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 |
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.
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