A test for additive outliers applicable to long-memory time series

About this item

Title

A test for additive outliers applicable to long-memory time series

Content partner

The University of Auckland Library

Collection

ResearchSpace@Auckland

Description

We propose a new test for additive outliers in Gaussian time series. The test statistic has a tractable asymptotic null distribution, namely the Gumbel distribution. It is calculated very simply without reference to parameters of any underlying model. The test is valid for a wide class of underlying stationary Gaussian series, and remains valid if the series being tested is pre-filtered by an invertible ARMA filter. To accelerate the convergence to the Gumbel distribution we introduce modifie...

Read more

Format

Research paper

Research format

Journal article

Date created

2006

Creator

Chareka, P / Matarise, F / Turner, Thomas

URL

http://hdl.handle.net/2292/16235

What is the copyright status of this item?

Share

See below for specifics about how you may use this item.

More Information

The University of Auckland Library has this to say about the rights status of this item:

Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. Details obtained from: http://www.sherpa.ac.uk/romeo/issn/0165-1889/

You can learn more about the rights status of this item at:

• https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm
• http://purl.org/eprint/accessRights/RestrictedAccess

What can I do with this item?

You must always check with The University of Auckland Library to confirm the specific terms of use, but this is our understanding:

Non-infringing use

NZ Copyright law does not prevent every use of a copyright work. You should consider what you can and cannot do with a copyright work.

Share it

This item is suitable for copying and sharing with others, without further permission.

No modifying

You are not allowed to adapt or remix this item into any other works.

No commercial use

You may not use this item commercially.