hidimstat.model_x_knockoff

hidimstat.model_x_knockoff(X, y, fdr=0.1, offset=1, method='equi', statistics='lasso_cv', shrink=False, centered=True, cov_estimator='ledoit_wolf', verbose=False, memory=None, n_jobs=1, seed=None)

Model-X Knockoff inference procedure to control False Discoveries Rate, based on Candes et al.[1]

Parameters:
X2D ndarray (n_samples, n_features)

design matrix

y1D ndarray (n_samples, )

response vector

fdrfloat, optional

desired controlled FDR level

offsetint, 0 or 1, optional

offset to calculate knockoff threshold, offset = 1 is equivalent to knockoff+

methodstr, optional

knockoff construction methods, either equi for equi-correlated knockoff or sdp for optimization scheme

statisticsstr, optional

method to calculate knockoff test score

shrinkbool, optional

whether to shrink the empirical covariance matrix

centeredbool, optional

whether to standardize the data before doing the inference procedure

cov_estimatorstr, optional

method of empirical covariance matrix estimation

seedint or None, optional

random seed used to generate Gaussian knockoff variable

Returns:
selected1D array, int

vector of index of selected variables

test_score1D array, (n_features, )

vector of test statistic

thresfloat

knockoff threshold

X_tilde2D array, (n_samples, n_features)

knockoff design matrix

References