Le modèle logistique - estimation

1. #Logit Regression
2. dt<-brabant[samp,]
3. attach(dt)
4. formula<-if_cde97 ~ r6 + rr6 + f6m + m6m + mm6m + caa96 + cda96
5. rfm.logit<-glm(formula,family=binomial)
6. par(mfrow=c(2,2))
7. plot(rfm.logit)
8. summary(rfm.logit)
9. dt<-brabant[-samp,]
10. attach(dt)
11. predictv<-predict(rfm.logit, type="response", newdata=dt)
12. names(predictv)<-1:length(predictv)
13. gc<-gainchart(predictv,dt$if_cde97)
14. par(mfrow=c(2,2))
15. plot_gaincharts(gc)