[Question] Cox model for ultra-high dimensional data about abess HOT 2 OPEN

Can you offer a minimal code to reproduce your report? Also, does your results is consistent with this paper: Principled sure independence screening for Cox models with ultra-high-dimensional covariates.

from abess.

Sorry about that, Here is the simulation code using jupyter notebook. And the performance of screening in abess package can not be as good as that in the cox-psis paper because the screening method in the paper can almost contain all the true features no matter how many features you want to choose. I append the result picture.

from abess import make_glm_data
from abess import CoxPHSurvivalAnalysis 
import numpy as np

sim = make_glm_data(n = 240, p = 7000, k = 20, family = 'cox', rho = 0.5, c = 60)
indice_real = np.array(np.where(sim.coef_ != 0)).reshape(-1)
print(indice_real)

cox = CoxPHSurvivalAnalysis(max_iter = 0,screening_size=1000,support_size=1000)
cox.fit(sim.x,sim.y)
indice_sc = np.array(np.where(cox.coef_ != 0)).reshape(-1)

inter = np.intersect1d(indice_sc,indice_real)
print(inter)

from abess.