Data tilting for time series

Peter Hall; Qiwei Yao

doi:10.1111/1467-9868.00394

Data tilting for time series

Peter Hall
, Qiwei Yao^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

Abstract

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'.

Original language	English
Pages (from-to)	425-442
Number of pages	18
Journal	Journal of the Royal Statistical Society. Series B: Statistical Methodology
Volume	65
Issue number	2
DOIs	https://doi.org/10.1111/1467-9868.00394
Publication status	Published - 2003

Access to Document

10.1111/1467-9868.00394

Cite this

@article{f6520c5e93bd4013a7b599d6a66f75a2,

title = "Data tilting for time series",

abstract = "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",

author = "Peter Hall and Qiwei Yao",

year = "2003",

doi = "10.1111/1467-9868.00394",

language = "English",

volume = "65",

pages = "425--442",

journal = "Journal of the Royal Statistical Society. Series B: Statistical Methodology",

issn = "1369-7412",

publisher = "Oxford University Press ",

number = "2",

}

TY - JOUR

T1 - Data tilting for time series

AU - Hall, Peter

AU - Yao, Qiwei

PY - 2003

Y1 - 2003

N2 - 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'.

AB - 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'.

KW - Autoregression

KW - Bootstrap

KW - Confidence interval

KW - Constrained inference

KW - Empirical likelihood

KW - Linear time series

KW - Power divergence

KW - Robust inference

UR - https://www.scopus.com/pages/publications/0038446328

U2 - 10.1111/1467-9868.00394

DO - 10.1111/1467-9868.00394

M3 - Article

SN - 1369-7412

VL - 65

SP - 425

EP - 442

JO - Journal of the Royal Statistical Society. Series B: Statistical Methodology

JF - Journal of the Royal Statistical Society. Series B: Statistical Methodology

IS - 2

ER -

Data tilting for time series

Abstract

Access to Document

Other files and links

Fingerprint

Cite this