Open AccessModerate deviations in subsampling distribution estimation
Author(s) -
Patrice Bertail,
Anthony Gamst,
Dimitris N. Politis
Publication year - 2000
Publication title -
proceedings of the american mathematical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.968
H-Index - 84
eISSN - 1088-6826
pISSN - 0002-9939
DOI - 10.1090/s0002-9939-00-05551-9
Subject(s) - quantile , distribution (mathematics) , annotation , semantics (computer science) , mathematics , sequence (biology) , statistics , computer science , algorithm , artificial intelligence , mathematical analysis , biology , genetics , programming language
In Politis and Romano (1994) the subsampling methodology was put forth for approximating the sampling distribution (and the corresponding quantiles) of general statistics from i.i.d. and stationary data. In this note, we address the question of how well the subsampling distribution approximates the tail of the target distribution. In the regular setting of the sample mean of an m m -dependent sequence we show a moderate deviation property of the subsampling distribution.