Central limit theorem under variance uncertainty
نویسندگان
چکیده
منابع مشابه
The central limit theorem under random truncation.
Under left truncation, data (X(i), Y(i)) are observed only when Y(i) ≤ X(i). Usually, the distribution function F of the X(i) is the target of interest. In this paper, we study linear functionals ∫ φ dF(n) of the nonparametric maximum likelihood estimator (MLE) of F, the Lynden-Bell estimator F(n). A useful representation of ∫ φ dF(n) is derived which yields asymptotic normality under optimal m...
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ژورنال
عنوان ژورنال: Electronic Communications in Probability
سال: 2015
ISSN: 1083-589X
DOI: 10.1214/ecp.v20-4341