Description Usage Arguments Value References See Also
This function calculates mu(Xk) for null replicates Xk.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 |
binary |
whether the response variable is binary (will be converted to factors if TRUE; default: FALSE). |
X |
a n by p matrix, containing all the covariates. |
i2 |
the index of inference samples. |
S |
a list of selected variables. |
out |
the fitted model from train.fun. |
nulls.list_S |
a list of length |S| whose element is a (|i2|*K)-dimensional vector, which contains K set of null samples. |
gamma_X.list_S |
a list of length |S|, with each element being the linear coefficient of the given covariate on the other covariates (only relevant when Xmodel = "gaussian"; default: NULL). |
useMC |
whether to use Monte Carlo estimators of the conditional quantities (default: TRUE). |
Xmodel |
model of the covaraites (default: "gaussian"). |
algo |
a fitting algorithm (default: "lasso"). |
predict.fun |
a function to produce predictions of the response variable with a given fitted model from train.fun and a matrix of new covariate values. |
cv.rule |
indicates which rule should be used for the predict function, either "min" (the usual rule) or "1se" (the one-standard- error rule); default: "min"). See the glmnet help files for details. |
verbose |
whether to show intermediate progress (default: FALSE). |
A list of kength |S|, whose element is the matrix of mu(Xk) with dimension n2-by-K or n2-by-1.
LZ-LJ:2020floodgate
Other methods:
calculate.V_mean()
,
fg.inference.binary()
,
fg.inference()
,
fit.mu()
,
floodgate.binary()
,
floodgate()
,
inference_general()
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