a_matrix(scan("diabetes.dat"),43,3,byrow=T)
a_a[sort.list(a[,1]),]
age_a[,1]
basedef_a[,2]
cpep_a[,3]
lncpep_log(cpep)

#Construct average kernel, loess and Supsmu curve estiamtors of
#lncpep on age.

par(mfrow=c(1,1))
plot(age,lncpep,ylab="ln(C_peptide)")
lines(ksmooth(age,lncpep,kernel="normal",bandwidth=5),lty=1)
lines(loess.smooth(age,lncpep,span=0.70,degree=1),lty=2)
lines(supsmu(age,lncpep,span="cv"),lty=4)
legend(7,1.3,lty=c(1,2,4),legend=c("Average Kernel (bandwidth=5)","Loess (span=0.7)",
"Supsmu Loess (CV)"))
title("Kernel Regerssion of ln(C_peptide) on age")

#Construct Loess fit and its 95% CI
par(mfrow=c(1,1))
plot(age,lncpep,ylab="ln(C_peptide)",xlab="Age",xlim=c(0,16),ylim=c(1.1,1.9))
fit_loess(lncpep~age,span=0.70,degree=1)
est_preplot(fit,confidence=20,coverage=0.95)
par(new=T)
plot(est,ylab=" ",xlab=" ",xlim=c(0,16),ylim=c(1.1,1.9))
title("Loess fit and its 95% CI")