THE KOMLÓS-MAJOR-TUSNÁDY APPROXIMATIONS AND THEIR APPLICATIONS
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Publication:3221111
DOI10.1111/j.1467-842X.1984.tb01233.xzbMath0557.60028OpenAlexW2149484219MaRDI QIDQ3221111
Publication date: 1984
Published in: Australian Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/j.1467-842x.1984.tb01233.x
Related Items (17)
Estimates for the quantiles of smooth conditional distributions and the multidimensional invariance principle ⋮ KMT coupling for random walk bridges ⋮ On the strong approximation of bootstrapped empirical copula processes with applications ⋮ Strong invariance principles for ergodic Markov processes ⋮ Large-sample study of the kernel density estimators under multiplicative censoring ⋮ Komlós-Major-Tusnády approximation under dependence ⋮ Estimates for the rate of strong Gaussian approximation for sums of i.i.d. multidimensional random vectors ⋮ Rate of strong Gaussian approximation for sums of i.i.d. multidimensional random vectors ⋮ Some applications of the strong approximation of the integrated empirical copula processes ⋮ Multidimensional version of the results of Komlos, Major and Tusnady for vectors with finite exponential moments ⋮ Nonstandard strong laws for local quantile processes ⋮ Strong approximation of multidimensional \(\mathbb P\)-\(\mathbb P\) plots processes by Gaussian processes with applications to statistical tests ⋮ Strong approximations for the \(p\)-fold integrated empirical process with applications to statistical tests ⋮ On the Bernstein-von Mises theorem for the Dirichlet process ⋮ Some asymptotic results for the integrated empirical process with applications to statistical tests ⋮ Strong approximation of empirical copula processes by Gaussian processes ⋮ The accuracy of strong Gaussian approximation for sums of independent random vectors
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