Internal pamr functions
pamr.pairscore(x, pair.ind=NULL)
pamr.pvalue.survival(group, survival.time, censoring.status, ngroup.survival)
pamr.score.to.class1(x, scores, cutoff=2, n.class=2)
pamr.score.to.class2(x, scores, cutoff=2, n.pc=1, n.class=2)
pamr.knnimpute.old(data, k = 10)
pamr.cube.root(x)
print.nsc(x, ...)
print.nsccv(x, ...)
# S3 method for pamrtrained
print(x, ...)
# S3 method for pamrcved
print(x, ...)
pamr.xl.error.trace()
pamr.xl.get.threshold.range(fit)
pamr.xl.get.soft.class.labels(fit, survival.times, censoring.status)
pamr.xl.compute.offset(data, offset.percent=50, prior=prior)
pamr.xl.get.offset()
pamr.xl.derive.adjusted.prior(prior, data)
pamr.xl.get.default.training.parameters(data)
pamr.xl.get.uniform.prior(data, nclasses=NULL)
pamr.xl.get.sample.prior(data)
pamr.xl.get.class.names()
pamr.xl.get.class.labels()
pamr.xl.get.number.of.classes()
pamr.xl.process.data(use.old.version=FALSE)
pamr.xl.compute.cv.confusion (fit, cv.results, threshold)
pamr.xl.compute.confusion (fit, threshold)
pamr.xl.is.a.subset(a, y)
pamr.xl.listgenes.compute (fit, data, threshold, fitcv=NULL, genenames = FALSE)
pamr.xl.plot.test.probs.compute(fit, new.x, newx.classes, missing.class.label,
threshold, sample.labels=NULL)
pamr.xl.plot.training.error.compute(trained.object)
pamr.xl.plotcen.compute(fit, data, threshold)
pamr.xl.plotcv.compute(aa)
pamr.xl.plotcvprob.compute(fit, data, threshold)
pamr.xl.predict.test.class(fit, newx, threshold, test.class.labels)
pamr.xl.predict.test.surv.class(fit, newx, threshold, survival.times,
censoring.status)
pamr.xl.predict.test.class.only(fit, newx, threshold)
pamr.xl.predict.test.probs(fit, newx, threshold)
pamr.xl.test.data.impute(x, k, use.old.version=FALSE)
pamr.xl.test.errors.surv.compute(fit, newx, threshold=fit$threshold,
survival.times, censoring.status)
pamr.xl.test.errors.compute(fit, newx, newx.classes, threshold=fit$threshold,
prior = fit$prior,
threshold.scale = fit$threshold.scale, ...)
pamr.xl.transform.class.labels(x)
pamr.xl.transform.data(data)
pamr.xl.transform.test.data(test.x)
pamr.xl.plotsurvival(fit, data, threshold)
pamr.xl.plotsurvival.test(fit, newx, survival.time, censoring.status, threshold)
pamr.xl.plotsurvival.strata(fit, data)
pamr.xl.test.get.soft.classes(fit, survival.times, censoring.status)
pamr.xl.get.soft.class.labels(fit, survival.times, censoring.status)These are not to be called by the user.