glmSparseNet.cox_: Call glmSparseNet model with Cox regression

In averissimo/glmSparseNetPaper:

Description

This is an auxiliary method for the analysis. It uses the run.cache method to cache the results and speed up analysis

Usage

glmSparseNet.cox_(xdata, ydata, target.vars, network = "correlation",
  xdata.digest = NULL, cache.prefix = "glmSparseNet.glmnet.model",
  force.recalc = FALSE, ...)

Arguments

xdata	input matrix
ydata	Surival data.dataframe with time and status columns
target.vars	number of variables to target in calculations
network	network to use, could be a matrix, a degree vector or a string, see ?glmSparseNet
xdata.digest	sha256 checksum of xdata
cache.prefix	prefix for the cache files
force.recalc	force cache to be recalculated

Value

a glmnet model

averissimo/glmSparseNetPaper documentation built on Jan. 25, 2021, 12:11 p.m.