Nothing
function.auto <-
function(data, marker, status, tag.healthy = 0, CFN, CFP, control = control.gsym.point(), confidence.level, seed, value.seed)
{
GPQ <- function.GPQ(data, marker, status, tag.healthy, CFN, CFP, control, confidence.level, seed, value.seed)
# If original data are normally distributed:
if (!"lambda" %in% names(GPQ))
{
res <- list (optimal.result = GPQ$optimal.result, AUC = GPQ$AUC, rho = GPQ$rho, pvalue.healthy = GPQ$pvalue.healthy, pvalue.diseased = GPQ$pvalue.diseased)
}
# If original data are not normally distributed:
if ("lambda" %in% names(GPQ))
{
# If transformed data are normally distributed:
if (GPQ$normality.transformed == "yes")
{
res <- list (optimal.result = GPQ$optimal.result, AUC = GPQ$AUC, rho = GPQ$rho, lambda = GPQ$lambda, normality.transformed = GPQ$normality.transformed, pvalue.healthy = GPQ$pvalue.healthy, pvalue.diseased = GPQ$pvalue.diseased, pvalue.healthy.transformed = GPQ$pvalue.healthy.transformed, pvalue.diseased.transformed = GPQ$pvalue.diseased.transformed)
}
# If transformed data are not normally distributed:
if (GPQ$normality.transformed == "no")
{
EL <- function.EL(data, marker, status, tag.healthy, CFN, CFP, control, confidence.level, seed, value.seed)
res <- list(optimal.result = EL$optimal.result, AUC = EL$AUC, rho = EL$rho, lambda = GPQ$lambda, normality.transformed= GPQ$normality.transformed, pvalue.healthy = GPQ$pvalue.healthy, pvalue.diseased = GPQ$pvalue.diseased, pvalue.healthy.transformed = GPQ$pvalue.healthy.transformed, pvalue.diseased.transformed = GPQ$pvalue.diseased.transformed)
}
}
return(res)
}
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