A Bootstrap Revival of Some Nonparametric Distance Tests

By Joseph P. Romano. 1988

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Exact and Approximate Stepdown Methods for Multiple Hypothesis Testing (2005, methodology): “Extensions to cases where τn depends on P are also possible, using ideas of Bertail, Politis, and Romano (1999). The bootstrap method relies on its ability to approximate the joint distribution of {τn[θ̂n,j − θj(P)] : j ∈ K}, whose distribution we denote by Jn,K(P).”
Control of generalized error rates in multiple testing (2007, background): “Hypothesis test constructions that do obey the constraints imposed by the null hypothesis, as discussed in [4] and [24], are”
Goodness‐of‐fit testing based on a weighted bootstrap: A fast large‐sample alternative to the parametric bootstrap (2012, methodology): “…orthants in Rd may appear as a natural choice for F in the goodness-of-fit framework under consideration, other choices might be of interest such as the class of indicator functions of closed balls, rectangles or half-spaces (see Romano, 1988, for a related discussion regarding the choice of F).”
Model Selection and Semiparametric Inference for Bivariate Failure-Time Data (2000, unknown): “Romano (1988) discussed the validity of using the bootstrap to approximate the asymptotic distribution of some general distance statistics.”
A test for the two-sample problem based on empirical characteristic functions (2008, background): “Præstgaard (1995) has considered a generalized version of the two-sample Kolmogorov–Smirnov test, which encompasses the ones in Bickel (1969) and Romano (1988, 1989).”
Comparing Probabilistic Forecasting Systems with the Brier Score (2007, methodology): “Romano (1988) describes a bootstrap test for exchangeability based on the maximum distance between the empirical distribution functions of the members and permuted members.”
Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models (2002, methodology): “Although estimation of nuisance parameters is not explicitly addressed in the present article, modi cations along the lines of Romano (1988) or theorem 19.”
Balanced Control of Generalized Error Rates (2010, background): “” Alternatively, hypothesis test constructions that do obey the constraints imposed by the null hypothesis, as discussed in [4] and [25], are based on the idea that the critical value should be obtained under the null hypothesis and so the resampling scheme should reflect the constraints of the null”
A New Coefficient of Correlation (2019, background): “There have been many proposals to address this deficiency of the classical coefficients [23], such as the maximal correlation coefficient [5, 15, 21, 33], various coefficients based on joint cumulative distribution functions and ranks [3, 4, 8, 9, 11, 14, 18, 22, 30, 32, 35, 36, 46–49], kernel-based”