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Empirical U-statistics processes
Journal of Statistical Planning and Inference, 1992Let \(\xi_ 1,\xi_ 2,\dots\) be independent and identically distributed random elements defined on a probability space \((\Omega,{\mathcal E},P)\) with values in a measurable space \(X_ 2\) with \(\sigma\)-field \(\mathcal A\) and let \(h: X^ q\to R^ r\) be an \(({\mathcal A}^ q,{\mathcal B}^ r)\)- measurable mapping \((q,r\in N)\) (\(h\) being ...
Ruymgaart, F.H., Zuijlen, M.C.A. van
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Tail probability approximations for U-statistics
Statistics & Probability Letters, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Keener, Robert W. +2 more
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2018
U statistics are a large and important class of statistics. Indeed, any U-statistic (with finite variance) is the non-parametric minimum variance estimator of its expectation \( \theta \). Many common statistics and estimators are either U-statistics or approximately so.
Arup Bose, Snigdhansu Chatterjee
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U statistics are a large and important class of statistics. Indeed, any U-statistic (with finite variance) is the non-parametric minimum variance estimator of its expectation \( \theta \). Many common statistics and estimators are either U-statistics or approximately so.
Arup Bose, Snigdhansu Chatterjee
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