Generates cluster data according to the used for supervised clustering
generate.cluster.data(ratio,npats=80,clusts=c(12,8,12,12,6),
sig=1,gamma=1,beta=c(-5,-2.5,0,2.5,5),outcomeModel=NULL)The ratio \(\tau^2/\sigma^2\) of the variance of the\ random effects to the error variance of the features
Number of observations in the data set.
The cluster identity of the features
The error variance of the features.
The error variance of the outcome.
The value of the regression coefficients
A function that returns a data frame with npats observations and rows that depend on the data object chosen. Two outcomeModel programs are provided, binaryOutcome and survivalOutcome, however users can write their own outcome model.
If NULL no data object is returned
A list with one element if outcomeModel=NULL which is a data frame which is npats times ngens+1 the last column is the outcome. Otherwise a list of two data frames, one being the feature data and the other being the outcome data according to what outcomeModel is used.