B. Appendix, R. Scilab, and . Codes, Plot AIC and BIC of Models versus Number of Variables in the Models varaic=[23;22;21;20;19;18;17;16;15;14;13;12;11;10;9;8; 7;6;5;4;3;2

. Xset, 1) xtitle("Difference between Pearson Error of Full and Final Models

$. Wealth=repay, $. Pcgmem=repay, $. Pcgmem-;-cbankmem=repay, . Cbankmem, C. Nolndpct et al., #==================================================# #++++++Data Ready for Logistic Regression++++++++++# dat<-data.frame(REP

B. Appendix, Scilab and R Codes p.err1; # error of test sample p.err2; # error of learning sample p.err3; # error of whole sample #=================================================================# #++++++++++++++++25 Samples-BIC Backward Stepwise++++++++++++++++# u=1:219, replace=TRUE, vol.160

. Optaichom, logit<-glm(REP~NOLNDPCT+SHARING+SHARNON+PRODCOOP+BIPCT +SNCTIONS+LNYRSOLD+PCGMEM+HOMOCCUP, data=dat, family=binomial()) summary(OptAicHOM.logit)

. Optaicavg, logit<-glm(REP~NOLNDPCT+SHARING+SHARNON+PRODCOOP+BIPCT +SNCTIONS+LNYRSOLD+PCGMEM+AVGED, data=dat, family=binomial()) summary(OptAicAVG.logit)

. Optaicvar, logit<-glm(REP~NOLNDPCT+SHARING+SHARNON+PRODCOOP+BIPCT +SNCTIONS+LNYRSOLD+PCGMEM+VARBTY, data=dat, family=binomial()) summary(OptAicVAR.logit)

. Optaicall3, . Rep~nolndpct+sharing+sharnon+prodcoop+bipct, . Sharnon, . Sharing, . Bipct et al., summary(OptAicall3.logit) #=================================================================# #+++++++++++++After Sampling BIC stepwise++++++++++++++++++++++++# #Add WEALTH to the BIC optimal Model OptBic.logit<-glm(REP~NOLNDPCT+ PRODCOOP+ SNCTIONS +LNYRSOLD+ PCGMEM, Pearson Errors of the Full and the Final Models #==========Pearson Errors of Full Model========# K=as.numeric(rep.logit$coefficients)#call the coefficients of the full model Beta0=as.matrix(K) # put the coefficients as matrix Xo=as, matrix(ndat) Yo=as.matrix(REP) pi=exp(Xo%*%Beta0)/(1+exp(Xo%*%Beta0))#fitted probability for y=1 a=pi*, p.1

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