A Bernstein-type inequality for \(U\)-statistics and \(U\)-processes
From MaRDI portal
Publication:1347184
DOI10.1016/0167-7152(94)00072-GzbMath0819.60021MaRDI QIDQ1347184
Publication date: 21 August 1995
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
empirical processesBernstein-type inequalityempirical distribution function\(U\)-statisticsdecouplinglocal oscillations
Related Items (22)
On local \(U\)-statistic processes and the estimation of densities of functions of several sample variables ⋮ Concordance and value information criteria for optimal treatment decision ⋮ Hoeffding-Serfling inequality for U-statistics without replacement ⋮ Hoeffding's inequality for sums of dependent random variables ⋮ Scaling by subsampling for big data, with applications to statistical learning ⋮ Analytical and statistical properties of local depth functions motivated by clustering applications ⋮ Uniform consistency and uniform in bandwidth consistency for nonparametric regression estimates and conditional U-statistics involving functional data ⋮ The performance of semi-supervised Laplacian regularized regression with the least square loss ⋮ UNIFORM BAHADUR REPRESENTATION FOR NONPARAMETRIC CENSORED QUANTILE REGRESSION: A REDISTRIBUTION-OF-MASS APPROACH ⋮ An adaptive composite quantile approach to dimension reduction ⋮ U-Processes and Preference Learning ⋮ A Bernstein-type inequality for functions of bounded interaction ⋮ A large deviation inequality for \(\beta\)-mixing time series and its applications to the functional kernel regression model ⋮ An Exponential Inequality for $U$-Statistics of I.I.D. Data ⋮ Multivariate spatial U-quantiles: A Bahadur-Kiefer representation, a Theil-Sen estimator for multiple regression, and a robust dispersion estimator ⋮ Quantile based dimension reduction in censored regression ⋮ Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm ⋮ Moderate and large deviations for \(U\)-processes ⋮ GLOBAL BAHADUR REPRESENTATION FOR NONPARAMETRIC CENSORED REGRESSION QUANTILES AND ITS APPLICATIONS ⋮ Unnamed Item ⋮ Uniform consistency and uniform in number of neighbors consistency for nonparametric regression estimates and conditional \(U\)-statistics involving functional data ⋮ Entropy and Concentration
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Limit theorems for \(U\)-processes
- Probability inequalities for empirical processes and a law of the iterated logarithm
- Characterization of the law of the iterated logarithm in Banach spaces
- A central limit theorem under metric entropy with \(L_ 2\) bracketing
- Empirical U-statistics processes
- Decoupling and Khintchine's inequalities for \(U\)-statistics
- Rates of convergence in the central limit theorem for empirical processes
- The sizes of compact subsets of Hilbert space and continuity of Gaussian processes
- Probability Inequalities for Sums of Bounded Random Variables
- Convergence of stochastic processes
This page was built for publication: A Bernstein-type inequality for \(U\)-statistics and \(U\)-processes
