Gini index is a measure of inequality and was developed to measure income
inequality in labour market. In the predictive model, Gini Index is used
for measuring discriminatory power.

blr_gini_index(model, data = NULL)

## Arguments

model |
An object of class `glm` . |

data |
A `tibble` or `data.frame` . |

## Value

Gini index.

## References

Siddiqi N (2006): Credit Risk Scorecards: developing and implementing intelligent
credit scoring. New Jersey, Wiley.

Müller M, Rönz B (2000): Credit Scoring using Semiparametric Methods. In: Franke J, Härdle W, Stahl G (Eds.):
Measuring Risk in Complex Stochastic Systems. New York, Springer-Verlag.

Kocenda E, Vojtek M (2011): Default Predictors in Retail Credit Scoring: Evidence from Czech
Banking Data. Forthcoming in: Emerging Markets Finance and Trade.

## See also

Other model validation techniques: `blr_confusion_matrix`

,
`blr_decile_capture_rate`

,
`blr_decile_lift_chart`

,
`blr_gains_table`

,
`blr_ks_chart`

,
`blr_lorenz_curve`

,
`blr_roc_curve`

,
`blr_test_hosmer_lemeshow`

## Examples

model <- glm(honcomp ~ female + read + science, data = hsb2,
family = binomial(link = 'logit'))
blr_gini_index(model)

#> [1] 0.5252134