locfit.censor {locfit}  R Documentation 
locfit.censor
produces local regression estimates for censored
data. The basic idea is to use an EM style algorithm, where one
alternates between estimating the regression and the true values
of censored observations.
locfit.censor
is designed as a front end
to locfit.raw
with data vectors, or as an intemediary
between locfit
and locfit.raw
with a
model formula. If you can stand the syntax, the second calling
sequence above will be slightly more efficient than the third.
locfit.censor(x, y, cens, ..., iter=3, km=FALSE)
x 
Either a locfit model formula or a numeric vector
of the predictor variable.

y 
If x is numeric, y gives the response variable.

cens 
Logical variable indicating censoring. The coding is 1
or TRUE for censored; 0 or FALSE for uncensored.

... 
Other arguments to locfit.raw

iter 
Number of EM iterations to perform 
km 
If km=TRUE , the estimation of censored observations uses
the KaplanMeier estimate, leading to a local version of the
BuckleyJames estimate. If km=F , the estimation is based
on a normal model (Schmee and Hahn). Beware of claims that BJ
is nonparametric; it makes stronger assumptions on the upper tail
of survival distributions than most authors care to admit.

"locfit"
object.
Buckley, J. and James, I. (1979). Linear Regression with censored data. Biometrika 66, 429436.
Loader, C. (1999). Local Regression and Likelihood. Springer, NY (Section 7.2).
Schmee, J. and Hahn, G. J. (1979). A simple method for linear regression analysis with censored data (with discussion). Technometrics 21, 417434.
data(heart) fit < locfit.censor(log10(surv+0.5)~age, cens=cens, data=heart) plotbyfactor(heart$age, 0.5+heart$surv, heart$cens, ylim=c(0.5,16000), log="y") lines(fit, tr=function(x)10^x)