groups.cv: Split a data set for cross-validation
In survJamda: Survival Prediction by Joint Analysis of Microarray Gene Expression Data

Description Usage Arguments Details Value Warning Author(s)

Define the folds of cross-validation.

1	groups.cv(n, ngroup, censor)

`n`	Sample size of a data set.
`ngroup`	Number of folds of cross-validation.
`censor`	Vector of censoring status. In the censoring status vector, 1 = event occurred, 0 = censored.

The function avoids allocating only censored patients to the testing set. At least one patient having experienced an event is needed for the applicability of the Cox proportional hazard model.

The folds of cross-validation.

This function is not called by the user directly.

Haleh Yasrebi

survJamda documentation built on May 1, 2019, 8:50 p.m.