Package: blorr 0.3.0.9000
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:
blorr_0.3.0.9000.tar.gz
blorr_0.3.0.9000.zip(r-4.5)blorr_0.3.0.9000.zip(r-4.4)blorr_0.3.0.9000.zip(r-4.3)
blorr_0.3.0.9000.tgz(r-4.4-x86_64)blorr_0.3.0.9000.tgz(r-4.4-arm64)blorr_0.3.0.9000.tgz(r-4.3-x86_64)blorr_0.3.0.9000.tgz(r-4.3-arm64)
blorr_0.3.0.9000.tar.gz(r-4.5-noble)blorr_0.3.0.9000.tar.gz(r-4.4-noble)
blorr_0.3.0.9000.tgz(r-4.4-emscripten)blorr_0.3.0.9000.tgz(r-4.3-emscripten)
blorr.pdf |blorr.html✨
blorr/json (API)
NEWS
| # Install 'blorr' in R: |
| install.packages('blorr', repos = c('https://rsquaredacademy.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rsquaredacademy/blorr/issues
- bank_marketing - Bank marketing data set
- hsb2 - High School and Beyond Data Set
- stepwise - Dummy Data Set
logistic-regression-modelsregression
Last updated 3 years agofrom:073f672bb8. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 07 2024 |
| R-4.5-win-x86_64 | OK | Sep 07 2024 |
| R-4.5-linux-x86_64 | OK | Sep 07 2024 |
| R-4.4-win-x86_64 | OK | Sep 07 2024 |
| R-4.4-mac-x86_64 | OK | Sep 07 2024 |
| R-4.4-mac-aarch64 | OK | Sep 07 2024 |
| R-4.3-win-x86_64 | OK | Sep 07 2024 |
| R-4.3-mac-x86_64 | OK | Sep 07 2024 |
| R-4.3-mac-aarch64 | OK | Sep 07 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.tableDerivdoBydplyrfansifarvergenericsggplot2gluegridExtragtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6RColorBrewerRcppRcppEigenrlangscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bank marketing data set | bank_marketing |
| 'blorr' package | blorr |
| Bivariate analysis | blr_bivariate_analysis blr_bivariate_analysis.default |
| Collinearity diagnostics | blr_coll_diag blr_eigen_cindex blr_vif_tol |
| Confusion matrix | blr_confusion_matrix blr_confusion_matrix.default |
| Event rate by decile | blr_decile_capture_rate |
| Decile lift chart | blr_decile_lift_chart |
| Gains table & lift chart | blr_gains_table plot.blr_gains_table |
| Gini index | blr_gini_index |
| KS chart | blr_ks_chart |
| Launch shiny app | blr_launch_app |
| Model specification error | blr_linktest |
| Lorenz curve | blr_lorenz_curve |
| Model fit statistics | blr_model_fit_stats |
| Multi model fit statistics | blr_multi_model_fit_stats blr_multi_model_fit_stats.default |
| Concordant & discordant pairs | blr_pairs |
| CI Displacement C vs fitted values plot | blr_plot_c_fitted |
| CI Displacement C vs leverage plot | blr_plot_c_leverage |
| Deviance vs fitted values plot | blr_plot_deviance_fitted |
| Deviance residual values | blr_plot_deviance_residual |
| DFBETAs panel | blr_plot_dfbetas_panel |
| CI Displacement C plot | blr_plot_diag_c |
| CI Displacement CBAR plot | blr_plot_diag_cbar |
| Delta chisquare plot | blr_plot_diag_difchisq |
| Delta deviance plot | blr_plot_diag_difdev |
| Fitted values diagnostics plot | blr_plot_diag_fit |
| Influence diagnostics plot | blr_plot_diag_influence |
| Leverage diagnostics plot | blr_plot_diag_leverage |
| Delta chi square vs fitted values plot | blr_plot_difchisq_fitted |
| Delta chi square vs leverage plot | blr_plot_difchisq_leverage |
| Delta deviance vs fitted values plot | blr_plot_difdev_fitted |
| Delta deviance vs leverage plot | blr_plot_difdev_leverage |
| Fitted values vs leverage plot | blr_plot_fitted_leverage |
| Leverage plot | blr_plot_leverage |
| Leverage vs fitted values plot | blr_plot_leverage_fitted |
| Residual values plot | blr_plot_pearson_residual |
| Residual vs fitted values plot | blr_plot_residual_fitted |
| Decile capture rate data | blr_prep_dcrate_data |
| KS Chart data | blr_prep_ksannotate_x blr_prep_ksannotate_y blr_prep_kschart_data blr_prep_kschart_line blr_prep_kschart_stat |
| Lift Chart data | blr_prep_lchart_data blr_prep_lchart_gmean |
| Lorenz curve data | blr_prep_lorenz_data |
| ROC curve data | blr_prep_roc_data |
| Binary logistic regression | blr_regress blr_regress.glm |
| Residual diagnostics | blr_residual_diagnostics |
| ROC curve | blr_roc_curve |
| Adjusted count R2 | blr_rsq_adj_count |
| Count R2 | blr_rsq_count |
| Cox Snell R2 | blr_rsq_cox_snell |
| Effron R2 | blr_rsq_effron |
| McFadden's R2 | blr_rsq_mcfadden |
| McFadden's adjusted R2 | blr_rsq_mcfadden_adj |
| McKelvey Zavoina R2 | blr_rsq_mckelvey_zavoina |
| Cragg-Uhler (Nagelkerke) R2 | blr_rsq_nagelkerke |
| Event rate | blr_segment blr_segment.default |
| Response distribution | blr_segment_dist plot.blr_segment_dist |
| Two way event rate | blr_segment_twoway blr_segment_twoway.default |
| Stepwise AIC backward elimination | blr_step_aic_backward blr_step_aic_backward.default plot.blr_step_aic_backward |
| Stepwise AIC selection | blr_step_aic_both plot.blr_step_aic_both |
| Stepwise AIC forward selection | blr_step_aic_forward blr_step_aic_forward.default plot.blr_step_aic_forward |
| Stepwise backward regression | blr_step_p_backward blr_step_p_backward.default plot.blr_step_p_backward |
| Stepwise regression | blr_step_p_both blr_step_p_both.default plot.blr_step_p_both |
| Stepwise forward regression | blr_step_p_forward blr_step_p_forward.default plot.blr_step_p_forward |
| Hosmer lemeshow test | blr_test_hosmer_lemeshow |
| Likelihood ratio test | blr_test_lr blr_test_lr.default |
| WoE & IV | blr_woe_iv plot.blr_woe_iv |
| Multi variable WOE & IV | blr_woe_iv_stats |
| High School and Beyond Data Set | hsb2 |
| Dummy Data Set | stepwise |
