eval.merge.simulate: Performance evaluation by merging two simulated independent...

In survJamda: Survival Prediction by Joint Analysis of Microarray Gene Expression Data

Description

Simulate two data sets, merge them and evaluate the performance of the gene signature derived from the merged data set in 10 iterations of 10-fold cross-validation. The data sets are combined into one set, split into the training and testing sets which are then normalized by Z-score normalization.

Usage

eval.merge.simulate(d1, d2, tot.genes, gene.nb, zscore)

Arguments

d1	Matrix of gene expression data of the first simulated data sets.
d2	Matrix of gene expression data of the second simulated data set.
tot.genes	Number of total genes.
gene.nb	Number of true survival genes to identify.
zscore	An integer (1 or 0) specifying whether to apply Z-score normalization or not.

Value

None.

Warning

This function is not called by the user directly.

Author(s)

Haleh Yasrebi

See Also

proc.simulate

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