generate.survival.data: Generate survival data.
In survJamda: Survival Prediction by Joint Analysis of Microarray Gene Expression Data

Description Usage Arguments Value Warning Author(s) See Also

Generate survival data following a Weibull model with specified parameters such as Cox coefficients and correlation among genes. Then, identify a gene signature and assess its performance in cross-validation.

1 2	generate.survival.data(gene.nb, tot.genes, sample.nb, beta.init, correlation, shape, scale)

`gene.nb`	The number of genes to select.
`tot.genes`	The total number of genes.
`sample.nb`	The total number of samples.
`beta.init`	Initial values for beta or Cox coefficients. The values between +/-0.5 to +/-3 are good choices.
`correlation`	Correlation among genes. The value should be between 0 and 1.
`shape`	Shape parameter of the Weibull model. Select a value between 1 and 5.
`scale`	Scale parameter of the Weibull model. Select a value between 1 and 5.

A list of three objects, (i) Matrix of simulated gene expression data, (ii) Vector of survival time and (iii) Vector of censoring status. In the censoring status vector, 1 = event occurred, 0 = censored.

This function is not called by the user directly.

Haleh Yasrebi

proc.simulate

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