SPEAKER:              Cong Chen
                      Iowa State University
                      
TITLE:                Spline estimators of the distribution function of
                           a variable measured with error

                           ABSTRACT

Three spline estimators are proposed to estimate the
density function of a random variable when the observation is
measured with error. The first is a weighted quantile regression
spline estimator. The other two are maximum likelihood spline 
estimators using the quantile regression spline estimator as an 
initial estimator. The proposed spline estimators perform better 
than a normal mixture estimator and better than a kernel 
estimator in a simulation study. The new estimation schemes are
applied to a nutrition data set and to a soil pH data set.