rsig.all(surv, X, model, n.rep.out = 10L, n.rep.in = 10L, plapply = mclapply, sd.filter = NULL)Surv] Survival object, see
Surv.data.frame] Data frame or matrix or
matrix of input data (rows: examples, columns:
features).character(1)] Model to use. One
of "rs.prlasso" (preconditioned lasso with robust
selection), "rs.lasso" (penalized Cox regression with
robust selection), "prlasso" (preconditioned lasso),
or "lasso" (penalized Cox regression)integer] The number of
replicates to be used to estimate selection probability
of features (outer subsampling)integer] The number of
replicates to be used for model aggregation (inner
subsampling)function] Function used for
internal parallelization. Default is
mclapply for multi-core parallel
execution.list] Pre-filter features by
their standard deviation, by one of the options
specified: topk: no. of features to be selected with
largest standard devations. quant: the min percentile
in standard deviations of features to be selected.rsig