Data tilting for time series

Authors: Hall P.; Yao Q.

Source: Journal of the Royal Statistical Society: Series B (Statistical Methodology), Volume 65, Number 2, May 2003 , pp. 425-442(18)

Publisher: Blackwell Publishing

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Abstract:

Summary.

We develop a general methodology for tilting time series data. Attention is focused on a large class of regression problems, where errors are expressed through autoregressive processes. The class has a range of important applications and in the context of our work may be used to illustrate the application of tilting methods to interval estimation in regression, robust statistical inference and estimation subject to constraints. The method can be viewed as ‘empirical likelihood with nuisance parameters’.

Keywords: Autoregression; Bootstrap; Confidence interval; Constrained inference; Empirical likelihood; Linear time series; Power divergence; Robust inference

Document Type: Research article

DOI: 10.1111/1467-9868.00394

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