Z-Process Method for Change Point Problems in Time Series

Ilia Negri ()
Additional contact information
Ilia Negri: University of Calabria

Chapter Chapter 15 in Research Papers in Statistical Inference for Time Series and Related Models, 2023, pp 381-388 from Springer

Abstract: Abstract Z-process method was introduced as a general unified approach based on partial estimation functions to construct a statistical test in change point problems not only for ergodic models but also for some non-ergodic models where the Fisher information matrix is random. In this paper, we consider the problem of testing for parameter changes in time series models based on this Z-process method. As an example, we consider the parameter change problem in some linear time series models. Some possibilities for nonlinear models are also discussed.

Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-99-0803-5_15

Ordering information: This item can be ordered from
http://www.springer.com/9789819908035

DOI: 10.1007/978-981-99-0803-5_15

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().