Prediction of hyper_gam model.
# S3 method for hyper_gam
predict(
object,
newdata = object$data,
sign_adjusted = TRUE,
sgn = if (sign_adjusted) sign(cor_xy(object, probs = 0.5)) else 1,
...
)Function predict.hyper_gam() returns a
double
an hyper_gam model
test hyperframe, with at least
the response \(y^{\text{new}}\) and
the double-hypercolumn \(X^{\text{new}}\)
tabulated on the same grid as the training hypercolumn \(X\).
If missing, the training data object$data will be used.
logical scalar, default TRUE
(internal use) numeric scalar, either -1 or 1,
the sign of cor_xy() return, to be used in the sign adjustment
additional parameters, currently not in use.
Function predict.hyper_gam() computes
the sign-adjusted gam model prediction.
The sign-adjustment ensures
that the return
is positively associated with the training hypercolumn \(X\)
at the selected tabulating grid.