I'm running the following code in r studio during which a cross-validation scheme selects the optimal bandwidth parameter for a set of data:
bw_object <- bwSelect(data = mood_data,
type = rep("g", 6),
level = rep(1, 6),
bwSeq = bwSeq,
bwFolds = 1,
bwFoldsize = 10,
modeltype = "mvar",
lags = 1,
scale = TRUE,
timepoints = time_data$time_norm,
beepvar = time_data$beepno,
dayvar = time_data$dayno,
pbar = TRUE)
Here's the error message I'm receiving:
Error in elnet(x, is.sparse, ix, jx, y, weights, offset, type.gaussian, :
y is constant; gaussian glmnet fails at standardization step
Please give me your thoughts. I have tried everything possible (ii.e. standardizing the variables, deleting stationary variables) and have had no luck!