| scr_align |
Stage 5: align a raw score to the declared scale |
| scr_apply |
Apply the WOE transformation or the scorecard to new data |
| scr_apply.scr_ead |
Apply the WOE transformation or the scorecard to new data |
| scr_apply.scr_lgd |
Apply the WOE transformation or the scorecard to new data |
| scr_apply.scr_pd |
Apply the WOE transformation or the scorecard to new data |
| scr_apply.scr_result |
Apply the WOE transformation or the scorecard to new data |
| scr_apply.scr_scorecard |
Apply the WOE transformation or the scorecard to new data |
| scr_bin |
Stage 2: optimal binning, screening, hold-out revalidation and pruning |
| scr_bin_continuous |
Bin drivers against a continuous target (LGD, CCF) |
| scr_calibrate |
Calibrate the alignment to a central tendency |
| scr_capital |
Expected loss, risk-weighted assets and capital of a portfolio |
| scr_classing_accept |
Accept or discard a proposal |
| scr_classing_apply |
Commit the lab into a new selection result |
| scr_classing_choose |
Choose the final variable list manually |
| scr_classing_discard |
Accept or discard a proposal |
| scr_classing_import |
Classing specification as a long table, with its file round trip |
| scr_classing_propose |
Propose manual bins for a variable |
| scr_classing_read |
Classing specification as a long table, with its file round trip |
| scr_classing_spec |
Classing specification as a long table, with its file round trip |
| scr_classing_view |
Inspect the current bins of a variable in the lab |
| scr_coarse_classing |
Coarse classing lab: manual binning and manual variable choice |
| scr_compare |
Compare runs across targets |
| scr_config |
Pipeline configuration |
| scr_config_keys |
Dictionary of configuration keys |
| scr_connect |
Connect to a database (ODBC DSN or any DBI driver) |
| scr_core |
Variables that cross several targets |
| scr_cutoff |
Stage 6: cut-off sweep with frozen cuts |
| scr_decisions |
Decision ledger of a lab, a result or a scorecard |
| scr_default |
Build the default flag from a monthly panel |
| scr_default_rate |
One-year default rates by cohort and the long-run average |
| scr_demo |
Synthetic example data |
| scr_demo_ead |
Synthetic monthly facility snapshots for the EAD/CCF module |
| scr_demo_lgd |
Synthetic default events for the workout LGD examples |
| scr_demo_lgd_cashflows |
Synthetic post-default cash flows of 'scr_demo_lgd' |
| scr_demo_panel |
Synthetic monthly panel for the default engine and PD calibration |
| scr_demo_portfolio |
Synthetic exposure snapshot for expected loss, capital and ECL |
| scr_demo_rates |
Synthetic monthly reference rate series |
| scr_ead |
Estimate CCF pools from the reference data set |
| scr_ead_data |
Build the realised-CCF reference data set from facility snapshots |
| scr_ead_downturn |
Downturn CCF per pool |
| scr_ead_validate |
Validate CCF pools: calibration, discrimination, back-testing and stability |
| scr_ecl |
Expected credit loss with stage allocation |
| scr_el |
Expected loss per exposure |
| scr_elbe |
ELBE and in-default LGD on a grid of months since default |
| scr_export |
Write the deliverables |
| scr_export.scr_capital |
Write the deliverables |
| scr_export.scr_classing |
Write the deliverables |
| scr_export.scr_ead |
Write the deliverables |
| scr_export.scr_lgd |
Write the deliverables |
| scr_export.scr_pd |
Write the deliverables |
| scr_export.scr_result |
Write the deliverables |
| scr_export.scr_scorecard |
Write the deliverables |
| scr_fetch |
Fetch a table with reproducible server-side sampling |
| scr_funnel |
Audit funnel: every input variable and its fate |
| scr_gains |
Gains table, at bin level |
| scr_grades |
Rating grades on the score |
| scr_irb_params |
IRB parameter tables by framework preset |
| scr_irb_rw |
IRB risk weight of one or many exposures |
| scr_iv |
Information Value of any grouping |
| scr_leakage |
Leakage and suspicious-strength audit |
| scr_lgd |
Two-stage LGD model and pools on the reference data set |
| scr_lgd_downturn |
Downturn LGD per pool |
| scr_lgd_floor |
Input floor on the downturn LGD per pool |
| scr_lgd_pools |
LGD pools from the predicted LGD |
| scr_lgd_validate |
Validation battery of an LGD model |
| scr_master_scale |
Master scale of PD grades |
| scr_metrics |
AUC, KS and Gini of a score, with a bootstrap confidence interval |
| scr_migration |
Migration matrix between two rating dates |
| scr_moc |
Margin of conservatism, by category |
| scr_model |
Stages 3 and 4: multi-strategy selection and consensus |
| scr_monitor |
Monitor the scorecard on new data |
| scr_monitoring_plan |
Monitoring plan read by scr_monitor() |
| scr_pd |
The PD model: grades, margin of conservatism and the floor |
| scr_pd_pit_ttc |
One-factor bridge between point-in-time and through-the-cycle PD |
| scr_pd_stress |
Stressed PD of the one-factor model |
| scr_pd_validate |
Validate a PD model on a cohort panel |
| scr_presets |
Selection presets, side by side |
| scr_psi |
Population stability index, with the fixed and the sample-size-adjusted threshold |
| scr_reasons |
Reason codes: the variables that took the most points from each row |
| scr_reject |
Stage 6: honest reject inference through a sensitivity band |
| scr_result |
Result of a selection |
| scr_run |
Run the selection for several targets straight from the database |
| scr_runset |
Set of runs, one per target |
| scr_sa_rw |
Standardised risk weight of an exposure |
| scr_scorecard |
Stages 4 and 5: points scorecard, aligned to the declared scale |
| scr_score_gains |
Score gains per frozen band |
| scr_score_metrics |
Score metrics per sample, with CI |
| scr_select |
Select variables for the scorecard |
| scr_selected |
Variables approved for the scorecard |
| scr_split |
Stage 0: type the data and split train and hold-out |
| scr_sql |
Production SQL |
| scr_sql.scr_capital |
Production SQL |
| scr_sql.scr_ead |
Production SQL |
| scr_sql.scr_lgd |
Production SQL |
| scr_sql.scr_pd |
Production SQL |
| scr_sql.scr_result |
Production SQL |
| scr_sql.scr_scorecard |
Production SQL |
| scr_strategy |
Stage 6: strategy table per band, with marginal expected profit |
| scr_triage |
Stage 1: descriptive triage and sentinel resolution |
| scr_verbose |
Switch progress messages on or off |
| scr_workout |
Workout LGD: the reference data set from default events and cash flows |
| summary.scr_result |
Result of a selection |
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