fg.inference.binary: Core procedure of floodgate: binary responses

In LuZhangH/floodgate: Floodgate: inference for model-free variable importance

Description

This function produces floodgate LCBs with given fitted mu (under binary responses).

Usage

fg.inference.binary(
  S,
  mu_X,
  mu_Xk,
  Y,
  M_n = NULL,
  one.sided = TRUE,
  alevel = 0.05,
  test = "z",
  verbose = TRUE
)

Arguments

S	a list of selected variables.
mu_X	a list of kength |S|, whose element is the matrix of mu(X) with dimension n2-by-1.
mu_Xk	a list of kength |S|, whose element is the matrix of mu(Xk) with dimension n2-by-K or n2-by-1.
Y	a n2 by 1 matrix, containing the response variables of the inferene samples.
M_n	the number of Monte Carlo samples for E(mu(X)|X-j).
one.sided	whether to obtain LCB or p-values via the one-sided way (default: TRUE).
alevel	confidence level (defaul: 0.05).
test	type of the hypothesis test (defaul: "z").
verbose	whether to show intermediate progress (default: FALSE).

Value

A list of three objects. inf.out: a matrix of |S|-by-4, containing the p-values, LCI, UCI and the floodgate LCB for variable in S; S: a list of selected variables.

References

\insertRef

LZ-LJ:2020floodgate

See Also

Other methods: calculate.V_mean(), calulate.mu_Xk(), fg.inference(), fit.mu(), floodgate.binary(), floodgate(), inference_general()

LuZhangH/floodgate documentation built on Aug. 30, 2020, 2:10 a.m.