An inverse probability weighted estimator for the bivariate distribution function under right censoring

Hongsheng Dai, Y. Bao

Research output: Contribution to journalArticle

Abstract

An inverse probability weighted estimator is proposed for the joint distribution function of bivariate random vectors under right censoring. The new estimator is based on the idea of transformation of bivariate survival functions and bivariate random vectors to univariate survival functions and univariate random variables. The estimator converges weakly to a zero-mean Gaussian process with an easily estimated covariance function. Numerical studies show that the new estimator is more efficient than some existing inverse probability weighted estimators.
Original languageEnglish
Pages (from-to)1789-1797
Number of pages9
JournalStatistics and Probability Letters
Volume79
Issue number16
DOIs
Publication statusPublished - 2009

Fingerprint Dive into the research topics of 'An inverse probability weighted estimator for the bivariate distribution function under right censoring'. Together they form a unique fingerprint.

  • Cite this