UMVU Estimation for Time Series

Xiaofei Xu (), Masanobu Taniguchi () and Naoya Murata ()
Additional contact information
Xiaofei Xu: Wuhan University
Masanobu Taniguchi: Waseda University
Naoya Murata: Waseda University

Chapter Chapter 25 in Research Papers in Statistical Inference for Time Series and Related Models, 2023, pp 555-564 from Springer

Abstract: Abstract This paper introduces the sufficiency, completeness, and uniformly minimum variance unbiased estimation for Gaussian circular ARMA processes. We propose a uniformly most powerful (UMP) test by monotone likelihood ratio for the coefficient parameter of the Gaussian circular AR(1) models. The numerical study shows good performance of the UMP test with composite null and composite alternative hypotheses for the Gaussian circular AR(1) models.

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_25

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

DOI: 10.1007/978-981-99-0803-5_25

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 ().