prototest: Inference on Prototypes from Clusters of Features

Procedures for testing for group-wide signal in clusters of variables. Tests can be performed for single groups in isolation (univariate) or multiple groups together (multivariate). Specific tests include the exact and approximate (un)selective likelihood ratio tests described in Reid et al (2015), the selective F test and marginal screening prototype test of Reid and Tibshirani (2015). User may pre-specify columns to be included in prototype formation, or allow the function to select them itself. A mixture of these two is also possible. Any variable selection is accounted for using the selective inference framework. Options for non-sampling and hit-and-run null reference distributions.

AuthorStephen Reid
Date of publication2016-04-19 08:59:44
MaintainerStephen Reid <sreid@stanford.edu>
LicenseGPL (>= 2)
Version1.1
http://arxiv.org/abs/1511.07839

View on CRAN

Files in this package

prototest
prototest/src
prototest/src/Makevars
prototest/src/hit_and_run.cpp
prototest/src/multivariate_alr.cpp
prototest/src/RcppExports.cpp
prototest/src/multivariate_elr.cpp
prototest/src/univariate_lr.cpp
prototest/NAMESPACE
prototest/R
prototest/R/nonselective.multivariate.F.test.R prototest/R/compute.test.statistic.R prototest/R/compute.lr.stat.multi.R prototest/R/find.root.R prototest/R/maximise.lr.R prototest/R/compute.selective.ts.and.p.val.R prototest/R/compute.QRS.vectors.R prototest/R/interval.if.derivative.always.positive.R prototest/R/update.mu.R prototest/R/compute.trunc.F.test.p.value.R prototest/R/enet.selection.A.b.R prototest/R/limits.exact.lr.R prototest/R/compute.mc.t.statistic.R prototest/R/update.theta.R prototest/R/update.sigma.R prototest/R/fit.enet.fixed.lambda.R prototest/R/compute.lr.stat.R prototest/R/update.theta.approx.R prototest/R/compute.approx.lr.R prototest/R/compute.non.selective.p.val.R prototest/R/limits.approx.lr.R prototest/R/print.prototest.R prototest/R/find.overall.truncation.interval.R prototest/R/compute.F.statistic.R prototest/R/hit.and.run.samples.multivariate.model.R prototest/R/find.where.sign.changes.R prototest/R/RcppExports.R prototest/R/truncation.region.function.R prototest/R/gradient.truncation.region.function.R prototest/R/mc.selection.A.b.R prototest/R/enet.selection.A.b.from.enet.R prototest/R/find.norm.limits.R prototest/R/find.single.truncation.interval.R prototest/R/interval.if.derivative.always.negative.R prototest/R/find.limits.R prototest/R/prototest.multivariate.R prototest/R/compute.mc.t.p.val.R prototest/R/nonselective.mc.test.R prototest/R/prototest.univariate.R prototest/R/compute.exact.lr.R
prototest/MD5
prototest/build
prototest/build/partial.rdb
prototest/DESCRIPTION
prototest/man
prototest/man/prototest.multivariate.Rd prototest/man/prototest.univariate.Rd prototest/man/print.prototest.Rd prototest/man/prototest-package.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.