estimategr | R Documentation |
A function used to estimate the reduced dimension regressions for g. The regression
can be computed using a user specified function, passed through SL.gr
or using
SuperLearner
when length(SL.gr) == 1
or is.list(SL.gr)
. There is
an error proofing of the SuperLearner
implementation that deals with situations where
the NNLS
procedure in the Super Learner ensemble fails and so the function returns
zero weights for every coefficient. In this case, the code will default to using the discrete
Super Learner; that is, the learner with lowest CV-risk.
estimategr(rg0, rg1, g0n, g1n, A0, A1, folds, validFold, Q2n, Q1n, SL.gr, abar,
return.models, tolg, verbose, ...)
rg0 |
The "residual" for the first reduced dimension regression (on Q1n). |
rg1 |
The "residual" for the second reduced dimension regression (on Q2n). |
g0n |
A |
g1n |
A |
A0 |
A |
A1 |
A |
folds |
Vector of cross-validation folds |
validFold |
Which fold is the validation fold |
Q2n |
A |
Q1n |
A |
SL.gr |
A |
abar |
A |
return.models |
A |
tolg |
A |
A list with elements g0nr, g1nr, h0nr, h1nr, and hbarnr, corresponding to the
predicted values of the reduced dimension regressions. Also included in output are the
models used to obtain these predicted values (set to NULL
if return.models = FALSE
)
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