prototest: Inference on Prototypes from Clusters of Features
Version 1.1

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
URL http://arxiv.org/abs/1511.07839
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("prototest")

Getting started

Package overview

Popular man pages

print.prototest: Print 'prototest' object
prototest.multivariate: Perform Prototype or F tests for Significance of Groups of...
prototest-package: Inference on Prototypes from Clusters of Features
prototest.univariate: Perform Prototype or F Tests for Significance of Groups of...
See all...

All man pages Function index File listing

Man pages

print.prototest: Print 'prototest' object
prototest.multivariate: Perform Prototype or F tests for Significance of Groups of...
prototest-package: Inference on Prototypes from Clusters of Features
prototest.univariate: Perform Prototype or F Tests for Significance of Groups of...

Functions

compute.F.statistic Source code
compute.QRS.vectors Source code
compute.approx.lr Source code
compute.exact.lr Source code
compute.lr.stat Source code
compute.lr.stat.multi Source code
compute.mc.t.p.val Source code
compute.mc.t.statistic Source code
compute.non.selective.p.val Source code
compute.selective.ts.and.p.val Source code
compute.test.statistic Source code
compute.trunc.F.test.p.value Source code
enet.selection.A.b Source code
enet.selection.A.b.from.enet Source code
find.limits Source code
find.norm.limits Source code
find.overall.truncation.interval Source code
find.root Source code
find.single.truncation.interval Source code
find.where.sign.changes Source code
fit.enet.fixed.lambda Source code
gradient.truncation.region.function Source code
hit.and.run.samples.multivariate.model Source code
interval.if.derivative.always.negative Source code
interval.if.derivative.always.positive Source code
limits.approx.lr Source code
limits.exact.lr Source code
maximise.lr Source code
mc.selection.A.b Source code
nonselective.mc.test Source code
nonselective.multivariate.F.test Source code
print.prototest Man page Source code
prototest Man page
prototest-package Man page
prototest.multivariate Man page Source code
prototest.univariate Man page Source code
rcpp_compute_lr_stat Source code
rcpp_generate_hit_and_run_samples Source code
rcpp_maximise_approx_likelihood Source code
rcpp_maximise_likelihood Source code
truncation.region.function Source code
update.mu Source code
update.sigma Source code
update.theta Source code
update.theta.approx Source code

Files

src
src/Makevars
src/hit_and_run.cpp
src/multivariate_alr.cpp
src/RcppExports.cpp
src/multivariate_elr.cpp
src/univariate_lr.cpp
NAMESPACE
R
R/nonselective.multivariate.F.test.R
R/compute.test.statistic.R
R/compute.lr.stat.multi.R
R/find.root.R
R/maximise.lr.R
R/compute.selective.ts.and.p.val.R
R/compute.QRS.vectors.R
R/interval.if.derivative.always.positive.R
R/update.mu.R
R/compute.trunc.F.test.p.value.R
R/enet.selection.A.b.R
R/limits.exact.lr.R
R/compute.mc.t.statistic.R
R/update.theta.R
R/update.sigma.R
R/fit.enet.fixed.lambda.R
R/compute.lr.stat.R
R/update.theta.approx.R
R/compute.approx.lr.R
R/compute.non.selective.p.val.R
R/limits.approx.lr.R
R/print.prototest.R
R/find.overall.truncation.interval.R
R/compute.F.statistic.R
R/hit.and.run.samples.multivariate.model.R
R/find.where.sign.changes.R
R/RcppExports.R
R/truncation.region.function.R
R/gradient.truncation.region.function.R
R/mc.selection.A.b.R
R/enet.selection.A.b.from.enet.R
R/find.norm.limits.R
R/find.single.truncation.interval.R
R/interval.if.derivative.always.negative.R
R/find.limits.R
R/prototest.multivariate.R
R/compute.mc.t.p.val.R
R/nonselective.mc.test.R
R/prototest.univariate.R
R/compute.exact.lr.R
MD5
build
build/partial.rdb
DESCRIPTION
man
man/prototest.multivariate.Rd
man/prototest.univariate.Rd
man/print.prototest.Rd
man/prototest-package.Rd
prototest documentation built on May 19, 2017, 4:45 p.m.

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