Approximations for a multivariate hybrid process with applications to change-point detection
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Publication:2437888
DOI10.3103/S106653071002002XzbMath1282.60038MaRDI QIDQ2437888
Publication date: 10 March 2014
Published in: Mathematical Methods of Statistics (Search for Journal in Brave)
rates of convergencepartial sumsnonparametric regressionchange-point detectionmultivariate empirical processes
Nonparametric regression and quantile regression (62G08) Bootstrap, jackknife and other resampling methods (62F40) Functional limit theorems; invariance principles (60F17)
Related Items (9)
Almost sure central limit theorem for the hybrid process ⋮ On the strong approximation of bootstrapped empirical copula processes with applications ⋮ On a weighted bootstrap approximation of the \(L_p\) norms of kernel density estimators ⋮ On the performance of weighted bootstrapped kernel deconvolution density estimators ⋮ A weighted bootstrap approximation of the maximal deviation of kernel density estimates over general compact sets ⋮ Asymptotic results for hybrids of empirical and partial sums processes ⋮ On the hybrids of \(k\)-spacing empirical and partial sum processes ⋮ On Complete Convergence for the Hybrid Process ⋮ Weighted bootstrapped kernel density estimators in two-sample problems
Cites Work
- A note on strong approximations of multivariate empirical processes
- A nonparametric test for the regression function: Asymptotic theory
- Approximations for hybrids of empirical and partial sums processes
- A large sample study of the Bayesian bootstrap
- Multivariate tests-of-fit and uniform confidence bands using a weighted bootstrap
- Comparing two failure time distributions in the presence of dependent censoring
- An approximation of partial sums of independent RV'-s, and the sample DF. I
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