Marcinkiewicz–Zygmund and ordinary strong laws for empirical distribution functions and plug-in estimators
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Publication:2934836
DOI10.1080/02331888.2013.800075zbMath1367.60024arXiv1301.0726OpenAlexW2962682367MaRDI QIDQ2934836
Publication date: 22 December 2014
Published in: Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1301.0726
empirical process\(\alpha\)-mixingplug-in estimatorlaw-invariant risk measureMarcinkiewicz-Zygmund strong law of large numbersstatistical functionalV-statisticsL-statisticfunction bracketordinary strong law of large numbers
Related Items (4)
Bootstrap consistency and bias correction in the nonparametric estimation of risk measures of collective risks ⋮ Continuous mapping approach to the asymptotics of \(U\)- and \(V\)-statistics ⋮ Comparative and qualitative robustness for law-invariant risk measures ⋮ Qualitative robustness of statistical functionals under strong mixing
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