Package: TMTI 1.0.3

Phillip B. Mogensen

TMTI: Too Many, Too Improbable (TMTI) Test Procedures

Methods for computing joint tests, controlling the Familywise Error Rate (FWER) and getting lower bounds on the number of false hypotheses in a set. The methods implemented here are described in Mogensen and Markussen (2021) <doi:10.48550/arXiv.2108.04731>.

Authors:Phillip B. Mogensen [aut, cre]

TMTI_1.0.3.tar.gz
TMTI_1.0.3.tar.gz(r-4.5-noble)TMTI_1.0.3.tar.gz(r-4.4-noble)
TMTI_1.0.3.tgz(r-4.4-emscripten)TMTI_1.0.3.tgz(r-4.3-emscripten)
TMTI.pdf |TMTI.html✨
TMTI/json (API)

# Install 'TMTI' in R:
install.packages('TMTI', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 66 downloads 20 exports 1 dependencies

Last updated 2 days agofrom:cfc56b9dd6. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-linux-x86_64OKOct 30 2024

Exports:adjust_LocalTestadjust_TMTICTP_LocalTestCTP_TMTIgamma_bootstrappergamma_bootstrapper_TtestkFWER_LocalTestkFWER_TMTIlocalTest_CTPrtTMTI_CDFTestSet_localTestTestSet_LocalTestTestSet_TMTITMTITMTI_CDFTMTI_CTPTopDown_localTestTopDown_LocalTestTopDown_TMTItTMTI_CDF

Dependencies:Rcpp

Readme and manuals

Help Manual

Help pageTopics
Adjust all p-values using a Closed Testing Procedure and a user-defined local test which satisfies the quadratic shortcut given in Mogensen and Markussen (2021)adjust_LocalTest
Adjust all p-values using a Closed Testing Procedeure and the TMTI family of tests.adjust_TMTI
A Closed Testing Procedure for any local test satisfying the conditions of Mogensen and Markussen (2021) using an O(n^2) shortcut.CTP_LocalTest localTest_CTP
A Closed Testing Procedure for the TMTI using an O(n^2) shortcutCTP_TMTI TMTI_CTP
Leading NAFullCTP_C
Leading NAFWER_set_C
Function to bootstrap the Cumulative Distribution Functions (CDFs) of the TMTI statistics.gamma_bootstrapper
Compute a list of TMTI CDFs for one- and two-sample test scenariosgamma_bootstrapper_Ttest
kFWER_LocalTest. Computes the largest rejection set possible with kFWER control.kFWER_LocalTest
Leading NAkFWER_set_C
kFWER_TMTI. Computes the largest rejection set possible with kFWER control.kFWER_TMTI
Leading NAMakeY_C
Leading NAMakeZ_C
Leading NAMakeZ_C_nsmall
Computes the analytical version of the rtMTI_infty CDF. When m>100, this should not be used.rtTMTI_CDF
Leading NATestSet_C
Test a subset of hypotheses in its closure using a user-specified local testTestSet_LocalTest TestSet_localTest
Test a subset of hypotheses in its closure using the TMTITestSet_TMTI
Computes the TMTI test for a joint hypothesis given input p-values.TMTI
Computes the analytical version of the TMTI_infty CDF. When m>100, this should not be used.TMTI_CDF
Leading NATopDown_C
Leading NATopDown_C_binary
Leading NATopDown_C_binary_subset
TopDown LocalTest algorithm for estimating a 1-alpha confidence set for the number of false hypotheses among a set.TopDown_LocalTest TopDown_localTest
TopDown TMTI algorithm for estimating a 1-alpha confidence set for the number of false hypotheses among a set.TopDown_TMTI
Computes the analytical version of the tTMTI_infty CDF. When m>100, this should not be used.tTMTI_CDF