An infinite dimensional convolution theorem with applications to random censoring and missing data models

DOI10.1016/0378-3758(90)90013-KzbMath0721.62035MaRDI QIDQ2641029

Anton Schick, V. Susarla

Publication date: 1990

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

zbMATH Keywords

random censoringlower boundmissing dataregular estimatorinfinite dimensional convolution theoremsMeier estimator

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Sufficiency and information (62B99)

Related Items

A central limit theorem for functionals of the Kaplan-Meier estimator, Best precedence tests for censored data, Some developments in semiparametric statistics

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