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The Bootstrap and Edgeworth Expansion
1: Principles of Bootstrap Methodology.- 2: Principles of Edgeworth Expansion.- 3: An Edgeworth View of the Bootstrap.- 4: Bootstrap Curve Estimation.- 5: Details of Mathematical Rigour.- Appendix I:Expand
On Some Simple Estimates of an Exponent of Regular Variation
SUMMARY We present a class of simple estimates of an exponent of regular variation. Unlike those proposed recently by de Haan and Resnick (1980), ours converge at an algebraic rather than aExpand
Optimal Rates of Convergence for Deconvolving a Density
Abstract Suppose that the sum of two independent random variables X and Z is observed, where Z denotes measurement error and has a known distribution, and where the unknown density f of X is to beExpand
Central limit theorem for integrated square error of multivariate nonparametric density estimators
Abstract Martingale theory is used to obtain a central limit theorem for degenerate U-statistics with variable kernels, which is applied to derive central limit theorems for the integrated squareExpand
Optimal Smoothing in Single-index Models
Single-index models generalize linear regression. They have applications to a variety of fields, such as discrete choice analysis in econometrics and dose response models in biometrics, whereExpand
Inference in ARCH and GARCH models with heavy-tailed errors
ARCH and GARCH models directly address the dependency of conditional second moments, and have proved particularly valuable in modelling processes where a relatively large degree of fluctuation isExpand
On blocking rules for the bootstrap with dependent data
SUMMARY We address the issue of optimal block choice in applications of the block bootstrap to dependent data. It is shown that optimal block size depends significantly on context, being equal toExpand
Nonparametric methods for inference in the presence of instrumental variables
We suggest two nonparametric approaches, based on kernel methods and orthogonal series, respectively, to estimating regression functions in the presence of instrumental variables. For the first timeExpand
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