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Groeneboom, P. (author), Maathuis, M.H. (author), Wellner, J.A. (author)
We study nonparametric estimation of the sub-distribution functions for current status data with competing risks. Our main interest is in the nonparametric maximum likelihood estimator (MLE), and for comparison we also consider a simpler “naive estimator.” Both types of estimators were studied by Jewell, van der Laan and Henneman [Biometrika ...
journal article 2008
document
Groeneboom, P. (author), Maathuis, M.H. (author), Wellner, J.A. (author)
We study nonparametric estimation for current status data with competing risks. Our main interest is in the nonparametric maximum likelihood estimator (MLE), and for comparison we also consider a simpler “naive estimator.” Groeneboom, Maathuis and Wellner [Ann. Statist. (2008) 36 1031–1063] proved that both types of estimators converge globally...
journal article 2008
document
Groeneboom, P. (author), Jongbloed, G. (author), Wellner, J.A. (author)
We study nonparametric estimation of convexregression and density functions by methods of least squares (in the regression and density cases) and maximum likelihood (in the density estimation case).We provide characterizations of these estimators, prove that they are consistent and establish their asymptotic distributions at a fixed point of...
journal article 2001
document
Groeneboom, P. (author), Jongbloed, G. (author), Wellner, J.A. (author)
A process associated with integrated Brownian motion is introduced that characterizes the limit behavior of nonparametric least squares and maximum likelihood estimators of convex functions and convex densities, respectively. We call this process “the invelope” and show that it is an almost surely uniquely defined function of integrated Brownian...
journal article 2001
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