Time series analysis of covariance based on linear transfer function models
M. Azimmohseni (),
M. Khalafi () and
M. Kordkatuli ()
Additional contact information
M. Azimmohseni: Golestan University
M. Khalafi: Golestan University
M. Kordkatuli: Golestan University
Statistical Inference for Stochastic Processes, 2019, vol. 22, issue 1, No 1, 16 pages
Abstract:
Abstract In this article, a time series analysis of covariance model is introduced when covariates time series have lead–lag relationship with response time series. Parameter estimation and hypothesis testing for this model are made in spectral domain. We provide an instruction for our approach using a real Hydrological time series data set.
Keywords: Discrete Fourier transform; Frequency response function; Prewhitening; Spectral representation; Transfer function model; Primary: 62M10; Secondary: 62M15 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s11203-018-9182-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:sistpr:v:22:y:2019:i:1:d:10.1007_s11203-018-9182-z
Ordering information: This journal article can be ordered from
http://www.springer. ... ty/journal/11203/PS2
DOI: 10.1007/s11203-018-9182-z
Access Statistics for this article
Statistical Inference for Stochastic Processes is currently edited by Denis Bosq, Yury A. Kutoyants and Marc Hallin
More articles in Statistical Inference for Stochastic Processes from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().