BayesPPR 0.2.0
BayesPPR 0.1.0.9000
- Fixed corrupted basis bookkeeping when resuming a fit whose last
draw contained a categorical ridge function (
bppr_resume()
failed outright).
- Fixed stale cached basis functions in
predict.bppr(),
which silently returned incorrect predictions when consecutive draws
shared the same number of ridge functions but used different features
for a categorical ridge.
- Fixed fitting failures when
X contains a constant
column and ncol(X) <= 3.
bppr() now accepts a data frame for X, as
documented.
bppr_pca() and predict.bppr_pca() no
longer fail when parallel::detectCores() returns
NA, and now validate par_type.
pca_setup() now bounds n_pc by
min(nrow(Y), ncol(Y)) instead of the maximum, and handles
prop_var = 1.
predict.bppr_pca() no longer fails when
newdata has a single row.
- Added validation of
idx_use, newdata
dimensions, w_feat, w_n_act, and missing
values in X/y.
BayesPPR 0.1.0