Package: blorr 0.3.1

Aravind Hebbali

blorr: Tools for Developing Binary Logistic Regression Models

Tools designed to make it easier for beginner and intermediate users to build and validate binary logistic regression models. Includes bivariate analysis, comprehensive regression output, model fit statistics, variable selection procedures, model validation techniques and a 'shiny' app for interactive model building.

Authors:Aravind Hebbali [aut, cre]

blorr_0.3.1.tar.gz
blorr_0.3.1.tar.gz(r-4.5-noble)blorr_0.3.1.tar.gz(r-4.4-noble)
blorr_0.3.1.tgz(r-4.4-emscripten)blorr_0.3.1.tgz(r-4.3-emscripten)
blorr.pdf |blorr.html
blorr/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/rsquaredacademy/blorr/issues

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

5.01 score 1 packages 143 scripts 1.6k downloads 3 mentions 71 exports 62 dependencies

Last updated 11 days agofrom:dc207793f4. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 13 2024
R-4.5-linux-x86_64OKNov 13 2024

Exports:blr_bivariate_analysisblr_coll_diagblr_confusion_matrixblr_decile_capture_rateblr_decile_lift_chartblr_eigen_cindexblr_gains_tableblr_gini_indexblr_ks_chartblr_launch_appblr_linktestblr_lorenz_curveblr_model_fit_statsblr_multi_model_fit_statsblr_pairsblr_plot_c_fittedblr_plot_c_leverageblr_plot_deviance_fittedblr_plot_deviance_residualblr_plot_dfbetas_panelblr_plot_diag_cblr_plot_diag_cbarblr_plot_diag_difchisqblr_plot_diag_difdevblr_plot_diag_fitblr_plot_diag_influenceblr_plot_diag_leverageblr_plot_difchisq_fittedblr_plot_difchisq_leverageblr_plot_difdev_fittedblr_plot_difdev_leverageblr_plot_fitted_leverageblr_plot_leverageblr_plot_leverage_fittedblr_plot_pearson_residualblr_plot_residual_fittedblr_prep_dcrate_datablr_prep_ksannotate_xblr_prep_ksannotate_yblr_prep_kschart_datablr_prep_kschart_lineblr_prep_kschart_statblr_prep_lchart_datablr_prep_lchart_gmeanblr_prep_lorenz_datablr_prep_roc_datablr_regressblr_residual_diagnosticsblr_roc_curveblr_rsq_adj_countblr_rsq_countblr_rsq_cox_snellblr_rsq_effronblr_rsq_mcfaddenblr_rsq_mcfadden_adjblr_rsq_mckelvey_zavoinablr_rsq_nagelkerkeblr_segmentblr_segment_distblr_segment_twowayblr_step_aic_backwardblr_step_aic_bothblr_step_aic_forwardblr_step_p_backwardblr_step_p_bothblr_step_p_forwardblr_test_hosmer_lemeshowblr_test_lrblr_vif_tolblr_woe_ivblr_woe_iv_stats

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11data.tableDerivdoBydplyrfansifarverFormulagenericsggplot2gluegridExtragtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6RColorBrewerRcppRcppEigenrlangscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr

A Short Introduction to the blorr Package

Rendered fromintroduction.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2024-11-11
Started: 2018-05-11

Readme and manuals

Help Manual

Help pageTopics
Bank marketing data setbank_marketing
Bivariate analysisblr_bivariate_analysis blr_bivariate_analysis.default
Collinearity diagnosticsblr_coll_diag blr_eigen_cindex blr_vif_tol
Confusion matrixblr_confusion_matrix blr_confusion_matrix.default
Event rate by decileblr_decile_capture_rate
Decile lift chartblr_decile_lift_chart
Gains table & lift chartblr_gains_table plot.blr_gains_table
Gini indexblr_gini_index
KS chartblr_ks_chart
Launch shiny appblr_launch_app
Model specification errorblr_linktest
Lorenz curveblr_lorenz_curve
Model fit statisticsblr_model_fit_stats
Multi model fit statisticsblr_multi_model_fit_stats blr_multi_model_fit_stats.default
Concordant & discordant pairsblr_pairs
CI Displacement C vs fitted values plotblr_plot_c_fitted
CI Displacement C vs leverage plotblr_plot_c_leverage
Deviance vs fitted values plotblr_plot_deviance_fitted
Deviance residual valuesblr_plot_deviance_residual
DFBETAs panelblr_plot_dfbetas_panel
CI Displacement C plotblr_plot_diag_c
CI Displacement CBAR plotblr_plot_diag_cbar
Delta chisquare plotblr_plot_diag_difchisq
Delta deviance plotblr_plot_diag_difdev
Fitted values diagnostics plotblr_plot_diag_fit
Influence diagnostics plotblr_plot_diag_influence
Leverage diagnostics plotblr_plot_diag_leverage
Delta chi square vs fitted values plotblr_plot_difchisq_fitted
Delta chi square vs leverage plotblr_plot_difchisq_leverage
Delta deviance vs fitted values plotblr_plot_difdev_fitted
Delta deviance vs leverage plotblr_plot_difdev_leverage
Fitted values vs leverage plotblr_plot_fitted_leverage
Leverage plotblr_plot_leverage
Leverage vs fitted values plotblr_plot_leverage_fitted
Residual values plotblr_plot_pearson_residual
Residual vs fitted values plotblr_plot_residual_fitted
Decile capture rate datablr_prep_dcrate_data
KS Chart datablr_prep_ksannotate_x blr_prep_ksannotate_y blr_prep_kschart_data blr_prep_kschart_line blr_prep_kschart_stat
Lift Chart datablr_prep_lchart_data blr_prep_lchart_gmean
Lorenz curve datablr_prep_lorenz_data
ROC curve datablr_prep_roc_data
Binary logistic regressionblr_regress blr_regress.glm
Residual diagnosticsblr_residual_diagnostics
ROC curveblr_roc_curve
Adjusted count R2blr_rsq_adj_count
Count R2blr_rsq_count
Cox Snell R2blr_rsq_cox_snell
Effron R2blr_rsq_effron
McFadden's R2blr_rsq_mcfadden
McFadden's adjusted R2blr_rsq_mcfadden_adj
McKelvey Zavoina R2blr_rsq_mckelvey_zavoina
Cragg-Uhler (Nagelkerke) R2blr_rsq_nagelkerke
Event rateblr_segment blr_segment.default
Response distributionblr_segment_dist plot.blr_segment_dist
Two way event rateblr_segment_twoway blr_segment_twoway.default
Stepwise AIC backward eliminationblr_step_aic_backward blr_step_aic_backward.default plot.blr_step_aic_backward
Stepwise AIC selectionblr_step_aic_both plot.blr_step_aic_both
Stepwise AIC forward selectionblr_step_aic_forward blr_step_aic_forward.default plot.blr_step_aic_forward
Stepwise backward regressionblr_step_p_backward blr_step_p_backward.default plot.blr_step_p_backward
Stepwise regressionblr_step_p_both blr_step_p_both.default plot.blr_step_p_both
Stepwise forward regressionblr_step_p_forward blr_step_p_forward.default plot.blr_step_p_forward
Hosmer lemeshow testblr_test_hosmer_lemeshow
Likelihood ratio testblr_test_lr blr_test_lr.default
WoE & IVblr_woe_iv plot.blr_woe_iv
Multi variable WOE & IVblr_woe_iv_stats
High School and Beyond Data Sethsb2
Dummy Data Setstepwise