Sparse Survival Dimension Reduction for High-Dimensional Censored Data


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Documentation for package ‘ssurvdr’ version 0.1.0

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compute_c1f_weights Compute basis-adaptive variable weights
compute_icomp Compute information criteria for reduced Cox model
evaluate_ssurvdr Evaluate ssurvdr fitted model against known simulation truth
extract_sdr_basis Extract sufficient dimension reduction basis
fit_reduced_cox Fit reduced Cox proportional hazards model
fit_ssurvdr Fit sparse survival dimension reduction model
fit_ssurvdr_grid Fit ssurvdr model over a tuning grid
fit_ssurvdr_sparse_path Fit an ICOMP-guided row-sparsity path
mec_covariance Maximum Entropy Covariance Estimator
run_ssurvdr_simulation Run Monte Carlo simulation for ssurvdr
save_kernel Compute survival SAVE kernel matrix
screen_survival_variables Screen variables using univariate Cox models
select_variables Select variables from SDR basis
simulate_ssurvdr Simulate high-dimensional censored survival data for ssurvdr
sparse_projection Sparse projection from SAVE kernel
sparsify_sdr_basis Row-sparsify an SDR basis
summarise_ssurvdr Summarise ssurvdr model output
survival_slicing Construct survival-informed slices for censored survival data