Description Usage Arguments Value
Hidden Covariates with Prior (HCP) implementation
1 |
data |
The data to be processed |
covariates |
Covariate matrix associated with samples |
k |
Specify number of hidden factors |
L1 |
Model parameter-penalty on ||Z-CU||_2^2. Here C denotes the scaled covariates |
L2 |
Model parameter-penalty on ||B||_2^2 |
L3 |
Model parameter-penalty on ||U||_2^2 |
max.iter |
Maximum number of iterations to perform |
trace |
Displace progress information or not |
return.all |
Return all reuslts or only the residual |
res |
Residual out of decomposition |
B |
Latent factors (if return.all=T) |
Z |
Loading matrix (if return.all=T) |
U |
Coefficient matrix for covariates (if return.all=T) |
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