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Monitoring the parameter changes in general ARIMA time series models

Yuzhi Cai Orcid Logo, Neville Davies

Journal of Applied Statistics, Volume: 30

Swansea University Author: Yuzhi Cai Orcid Logo

Abstract

We propose methods for monitoring theresiduals of a fitted ARIMA or an autoregressive fractionallyintegrated movingaverage ($ARFIMA$) model in order to detect changes of the parametersin that model. We extend the procedures of Box \& Ramirez (1992) andRamirez(1992) and allow the differencing par...

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Published in: Journal of Applied Statistics
Published: 2003
URI: https://cronfa.swan.ac.uk/Record/cronfa15299
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last_indexed 2019-10-17T13:16:54Z
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spelling 2019-10-17T09:48:16.9103516 v2 15299 2013-07-30 Monitoring the parameter changes in general ARIMA time series models eff7b8626ab4cc6428eef52516fda7d6 0000-0003-3509-9787 Yuzhi Cai Yuzhi Cai true false 2013-07-30 BAF We propose methods for monitoring theresiduals of a fitted ARIMA or an autoregressive fractionallyintegrated movingaverage ($ARFIMA$) model in order to detect changes of the parametersin that model. We extend the procedures of Box \& Ramirez (1992) andRamirez(1992) and allow the differencing parameter, $d$ to be fractional or integer. Test statistics are approximated by Wiener processes. We carry out simulations and also apply our method to several real time series. The results show that our method is effective for monitoring all parameters in $ARFIMA$ models. Journal Article Journal of Applied Statistics 30 1001 ARIMA, autoregressive fractionally integrated moving average; time series; CUSCORE; changes of parameters; simulation. 30 6 2003 2003-06-30 COLLEGE NANME Accounting and Finance COLLEGE CODE BAF Swansea University 2019-10-17T09:48:16.9103516 2013-07-30T11:16:48.1103909 Faculty of Humanities and Social Sciences School of Management - Accounting and Finance Yuzhi Cai 0000-0003-3509-9787 1 Neville Davies 2
title Monitoring the parameter changes in general ARIMA time series models
spellingShingle Monitoring the parameter changes in general ARIMA time series models
Yuzhi Cai
title_short Monitoring the parameter changes in general ARIMA time series models
title_full Monitoring the parameter changes in general ARIMA time series models
title_fullStr Monitoring the parameter changes in general ARIMA time series models
title_full_unstemmed Monitoring the parameter changes in general ARIMA time series models
title_sort Monitoring the parameter changes in general ARIMA time series models
author_id_str_mv eff7b8626ab4cc6428eef52516fda7d6
author_id_fullname_str_mv eff7b8626ab4cc6428eef52516fda7d6_***_Yuzhi Cai
author Yuzhi Cai
author2 Yuzhi Cai
Neville Davies
format Journal article
container_title Journal of Applied Statistics
container_volume 30
publishDate 2003
institution Swansea University
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Accounting and Finance{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Accounting and Finance
document_store_str 0
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description We propose methods for monitoring theresiduals of a fitted ARIMA or an autoregressive fractionallyintegrated movingaverage ($ARFIMA$) model in order to detect changes of the parametersin that model. We extend the procedures of Box \& Ramirez (1992) andRamirez(1992) and allow the differencing parameter, $d$ to be fractional or integer. Test statistics are approximated by Wiener processes. We carry out simulations and also apply our method to several real time series. The results show that our method is effective for monitoring all parameters in $ARFIMA$ models.
published_date 2003-06-30T03:17:26Z
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score 10.997933

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