Package: sigr 1.1.5

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John Mount

sigr: Succinct and Correct Statistical Summaries for Reports

Succinctly and correctly format statistical summaries of various models and tests (F-test, Chi-Sq-test, Fisher-test, T-test, and rank-significance). This package also includes empirical tests, such as Monte Carlo and bootstrap distribution estimates.

Authors:John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]

sigr_1.1.5.tar.gz
sigr_1.1.5.zip(r-4.6)sigr_1.1.5.zip(r-4.5)sigr_1.1.5.zip(r-4.4)
sigr_1.1.5.tgz(r-4.5-any)
sigr_1.1.5.tar.gz(r-4.6-any)sigr_1.1.5.tar.gz(r-4.5-any)
sigr_1.1.5.tgz(r-4.5-emscripten)
sigr.pdf |sigr.html✨
sigr/json (API)
NEWS

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

Bug tracker:https://github.com/winvector/sigr/issues

Pkgdown/docs site:https://winvector.github.io

On CRAN:

Conda:

6.95 score 28 stars 1 packages 105 scripts 672 downloads 1 mentions 54 exports 1 dependencies

Last updated from:019233dfbb. Checks:9 OK. Indexed: yes.

TargetResultTotal timeArtifact
linux-devel-x86_64OK99
source / vignettesOK192
linux-release-x86_64OK120
macos-release-arm64OK95
macos-oldrel-arm64OK85
windows-develOK80
windows-releaseOK77
windows-oldrelOK74
wasm-releaseOK95

Exports:%:=%%.>%add_ROC_derived_columnsapply_leftapply_rightBernoulli_diff_statbuild_framebuild_ROC_curvecalcAUCcalcDeviancecalcSSEcheck_utility_calcdraw_frameestimateDifferenceZeroCrossingfind_area_qfind_AUC_qfind_matching_a1_1bfind_matching_conditional_betasfind_ROC_matching_abfind_ROC_matching_ab1fit_beta_shapesgetRenderingFormatletmap_to_charmk_tmp_name_sourcemodel_utilitypermTestAUCpermutationScoreModelqaeqcqchar_frameqerenderresampleScoreModelresampleScoreModelPairresampleTestAUCsensitivity_and_specificity_s12p12nsensitivity_from_specificity_qtestAUCpairTIntervalTIntervalSwrapBinomTestwrapBinomTestSwrapChiSqTestwrapChiSqTestImplwrapCohenDwrapCorTestwrapFisherTestwrapFTestwrapFTestezANOVAwrapFTestImplwrapPWRwrapSignificancewrapTTest

Dependencies:wrapr

lm example

John Mount

Rendered fromlmExample.Rmdusingknitr::rmarkdownon Nov 24 2025.

Last update: 2018-07-16
Started: 2017-03-03

sigr formatting

John Mount

Rendered fromsigrFormatting.Rmdusingknitr::rmarkdownon Nov 24 2025.

Last update: 2023-08-20
Started: 2016-10-07

Readme and manuals

Help Manual

Help pageTopics
sigr: Format Significance Summaries for Reportssigr-package sigr
Add ROC derived columns.add_ROC_derived_columns
as.characteras.character.sigr_statistic
Compute the distribution of differences of replacement samples of two Binomial or Bernoulli experiments.Bernoulli_diff_stat
calculate ROC curve.build_ROC_curve
calculate AUC.calcAUC
Calculate deviance.calcDeviance
Calculate sum of squared error.calcSSE
Studentized estimate of how often a difference is below zero.estimateDifferenceZeroCrossing
Find area matching polynomial curve.find_area_q
Find area matching polynomial curve.find_AUC_q
Find beta-1 shape parameters matching the conditional distributions.find_matching_a1_1b find_ROC_matching_ab1
Find beta shape parameters matching the conditional distributions.find_matching_conditional_betas find_ROC_matching_ab
Fit beta parameters from data.fit_beta_shapes
Formatformat.sigr_statistic
Detect rendering format (using knitr).getRenderingFormat
Estimate model utilitymodel_utility
Perform AUC permutation test.permTestAUC
Empirical permutation test of significance of scoreFn(modelValues,yValues) >= scoreFn(modelValues,perm(yValues)).permutationScoreModel
Printprint.sigr_statistic
Format summary roughly in "APA Style" ( American Psychological Association ).render
Format an AUC-test (quality of a probability score)render.sigr_aucpairtest
Format an AUC-test (quality of a probability score)render.sigr_aucpermtest
Format an AUC-test (quality of a probability score)render.sigr_aucresamptest
Format sigr_Bernoulli_diff_test (test of difference of Bernoulli processes).render.sigr_Bernoulli_diff_test
Format binom.test (test of rate of a Binomial/Bernoulli experiment).render.sigr_binomtest
Format a chi-square test (quality of categorical prediction)render.sigr_chisqtest
Format Cohen-D (effect size between groups)render.sigr_cohend
Format cor.test (test of liner correlation).render.sigr_cortest
Format an empirical test (quality of categorical prediction)render.sigr_emptest
Format fisher.test (test of categorical independence).render.sigr_fishertest
Format an F-testrender.sigr_ftest
Format an empirical test (quality of categorical prediction)render.sigr_permtest
Format a pwr-testrender.sigr_pwr_htest
Format a significancerender.sigr_significance
Format a Student-T tolerance-style interval around an estimate of a mean.render.sigr_tinterval
Format a T-test (difference in means by group)render.sigr_ttest
Studentized bootstrap variance estimate for scoreFn(yValues,modelValues).resampleScoreModel
Studentized bootstrap test of strength of scoreFn(yValues,model1Values) > scoreFn(yValues,model1Values).resampleScoreModelPair
Wrap AUC resampling test results.resampleTestAUC
Compute the shape1_pos, shape2_pos, shape1_neg, shape2_neg graph.sensitivity_and_specificity_s12p12n
Compute the q-graph.sensitivity_from_specificity_q
Test AUC pair results.testAUCpair
Wrap TInterval (test of Binomial/Bernoulli rate).TInterval
Student-T tolerance-style interval around an estimate of a mean from a data.frame.TInterval.data.frame
Student-T tolerance-style interval around an estimate of a mean from observations.TInterval.numeric
Student-T tolerance-style interval around an estimate of a mean from summary.TIntervalS
Wrap binom.test (test of Binomial/Bernoulli rate).wrapBinomTest
Wrap binom.test (test of Binomial/Bernoulli rate).wrapBinomTest.data.frame
Wrap binom.test (test of Binomial/Bernoulli rate).wrapBinomTest.htest
Wrap binom.test (test of Binomial/Bernoulli rate).wrapBinomTest.logical
Wrap binom.test (test of Binomial/Bernoulli rate).wrapBinomTest.numeric
Wrap binom.test (test of Binomial/Bernoulli rate) from summary.wrapBinomTestS
Wrap quality of a categorical prediction roughly in "APA Style" ( American Psychological Association ).wrapChiSqTest
Format ChiSqTest from anova of logistic model.wrapChiSqTest.anova
Format ChiSqTest from data.wrapChiSqTest.data.frame
Format ChiSqTest from model.wrapChiSqTest.glm
Format ChiSqTest from model summary.wrapChiSqTest.summary.glm
Format quality of a logistic regression roughly in "APA Style" ( American Psychological Association ).wrapChiSqTestImpl
Wrap Cohen's D (effect size between groups).wrapCohenD
Wrap Cohen's D (effect size between groups).wrapCohenD.data.frame
Wrap Cohen's D (effect size between groups).wrapCohenD.numeric
Wrap cor.test (test of liner correlation).wrapCorTest
Wrap cor.test (test of liner correlation).wrapCorTest.data.frame
Wrap cor.test (test of liner correlation).wrapCorTest.htest
Wrap fisher.test (test of categorical independence).wrapFisherTest
Wrap fisher.test (test of categorical independence).wrapFisherTest.data.frame
Wrap fisher.test (test of categorical independence).wrapFisherTest.htest
Wrap fisher.test (test of categorical independence).wrapFisherTest.table
Wrap F-test (significance identity relation).wrapFTest
Wrap quality statistic of a linear relation from anova.wrapFTest.anova
Wrap quality statistic of identity relation from data.wrapFTest.data.frame
Wrap F-test (ratio of variances).wrapFTest.htest
Wrap quality statistic of identity r regression.wrapFTest.lm
Wrap quality statistic of linear regression summary.wrapFTest.summary.lm
Wrap quality statistic of a linear relation from ezANOVA (package ez).wrapFTestezANOVA
Wrap F-test (significance of identity relation).wrapFTestImpl
Wrap pwr test (difference in means by group).wrapPWR
Wrap pwr test.wrapPWR.power.htest
Wrap a significancewrapSignificance
Wrap t.test (difference in means by group).wrapTTest
Wrap t.test (difference in means by group).wrapTTest.data.frame
Wrap t.test (difference in means by group).wrapTTest.htest
Wrap t.test (difference in means by group).wrapTTest.numeric
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