cov_nnls {fastFMM} | R Documentation |
Helper function for 'G_estimate'. Uses least squares under non-negativity constraints, mainly relying on 'nnls' capability from 'lsei'.
cov_nnls(
data,
L,
out_index,
data_cov,
RE_table,
idx_lst,
designmat,
betaHat,
GTilde,
non_neg = 0,
silent = TRUE
)
data |
Data frame containing all predictor and outcome variables |
L |
The dimension of the functional domain |
out_index |
Indices of outcome variables in 'data' |
data_cov |
(unsure) Covariance of variables |
RE_table |
Data frame containing random effects and interactions |
idx_lst |
(unsure) Column indices of random effects |
designmat |
(unsure) |
betaHat |
Estimates of coefficients of random effects |
GTilde |
Current 'GTilde' estimate, created as an intermediate in 'G_estimate' |
non_neg |
(unsure), defaults to 0 |
silent |
Whether to print the step. Defaults to 'TRUE'. |
A matrix with the same dimensions as 'GTilde'.