Nonparametric estimation of a distribution function under biased sampling and censoring

Details Nonparametric estimation of a distribution function under biased sampling and censoring Nonparametric estimation of a distribution function under biased sampling and censoring

2007-08-08

arxiv.org/abs/0708.1061v1

IMS Lecture Notes Monograph Series 2007, Vol. 54, 224-238

Mathematics

Statistics Theory

Published at http://dx.doi.org/10.1214/074921707000000175 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/p

Scientific paper

10.1214/074921707000000175

This paper derives the nonparametric maximum likelihood estimator (NPMLE) of a distribution function from observations which are subject to both bias and censoring. The NPMLE is obtained by a simple EM algorithm which is an extension of the algorithm suggested by Vardi (Biometrika, 1989) for size biased data. Application of the algorithm to many models is discussed and a simulation study compares the estimator's performance to that of the product-limit estimator (PLE). An example demonstrates the utility of the NPMLE to data where the PLE is inappropriate.

Affiliated with

Also associated with

No associations

Rating

Nonparametric estimation of a distribution function under biased sampling and censoring does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Nonparametric estimation of a distribution function under biased sampling and censoring, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Nonparametric estimation of a distribution function under biased sampling and censoring will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-215537