hello > p(X ≤ V) diffetente zero > look this > Let X and V be two independent random variables with unknow > distribution functions (d.f.’s) F and G respectively. Under truncation from >the right we observe (X, Z) only if X ≤ Z > I simulate X and Z and I use Lynden bell estimation > I need now to calculate alpha =p(X ≤ V)but no p(X ≤ V)=0 >
> > > > > > > > for exampl, i have this programme > > # Generating data which are right truncated > > library(DTDA) > > library(splines) > > library(survival) > > n<-25 > > X<-runif(n,0,1) > > V<-runif(n,0.75,1) > > for (i in 1:n){ > > while (X[i]>V[i]){ > > X[i]<-runif(1,0,1) > > V[i]<-runif(1,0.75,1) > > }} > > res<-lynden(X=X,U=NA, V=V, boot=TRUE) > > attach(res) > > temps = time > > M_i = n.event > > L_t = res > > F_t=1-L_t > > par(mfrow=c(1,1)) > > plot(L_t$time,L_t$survival,type="s",lty=2:3,lwd=2,las=1,cex.lab=1.1,font.lab=2,col="red",xlab="temps",ylab="L(t)", > > > main="Esitmation de la Fonction de Survie L(t)") [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.