A weak invariance principle for weighted \(U\)-statistics with varying kernels

DOI10.1006/jmva.1993.1072zbMath0788.60045OpenAlexW2021397658MaRDI QIDQ689368

Thomas Mikosch

Publication date: 6 December 1993

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1006/jmva.1993.1072

zbMATH Keywords

Gaussian processes\(U\)-statisticsLévy-Prokhorov distanceweak limit theorems of functional type

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Central limit and other weak theorems (60F05) Functional limit theorems; invariance principles (60F17)

Related Items (5)

Asymptotic normality of quadratic estimators ⋮ A \(U\)-classifier for high-dimensional data under non-normality ⋮ Adaptive nonparametric confidence sets ⋮ The multivariate functional de Jong CLT ⋮ Semiparametric estimation of moment condition models with weakly dependent data

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