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Subsampling p-values
(2010)
A construction of p-values for hypothesis tests based on subsampling and the related m out of n bootstrap is introduced. The p-values are based on a modification of the usual subsampling hypothesis tests that involves an ...
Subsampling Inference with K Populations and a Non-standard Behrens-Fisher Problem
(2012)
We revisit the methodology and historical development of subsampling, and then explore in detail its use in hypothesis testing, an area which has received surprisingly modest attention. In particular, the general set-up ...
Nonparametric regression with infinite order flat-top kernels
(2004)
The problem of nonparametric regression is addressed, and a kernel smoothing estimator is proposed which has favorable asymptotic performance (bias, variance and mean squared error). The proposed class of kernels is ...
Banded and tapered estimates for autocovariance matrices and the linear process bootstrap
(2010)
We address the problem of estimating the autocovariance matrix of a stationary process. Under short range dependence assumptions, convergence rates are established for a gradually tapered version of the sample autocovariance ...
High-dimensional autocovariance matrices and optimal linear prediction
(2015)
A new methodology for optimal linear prediction of a stationary time series is introduced. Given a sample X1,…,Xn, the optimal linear predictor of Xn+1 is Xn+1 = Φ1(n)Xn + Φ2(n)Xn−1 + + Φn(n)X1. In practice, the coefficient ...
Bootstrap confidence intervals in nonparametric regression with built-in bias correction
(2008)
The problem of estimating nonparametric regression with associated confidence intervals is addressed. It is shown that through appropriate choice of infinite order kernel, it is possible to construct bootstrap confidence ...