Journal
BIOMETRIKA
Volume 88, Issue 2, Pages 381-390Publisher
BIOMETRIKA TRUST
DOI: 10.1093/biomet/88.2.381
Keywords
bootstrap; heteroscedastic regression; L-p norm; resampling method; truncated regression; U-process
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Suppose that under a semiparametric setting an estimator of a vector of parameters of interest is obtained by optimising an objective function which has a U-process structure. The covariance matrix of the estimator is generally a function of the underlying density function, which may be difficult to estimate well by conventional methods. In this paper, we present a simple resampling method by perturbing the objective function repeatedly. Inferences of the parameters can then be made based on a large collection of the resulting optimisers. We illustrate our proposal by three examples with a heteroscedastic regression model.
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