Previous |  Up |  Next

Article

Title: Periodic autoregression with exogenous variables and periodic variances (English)
Author: Anděl, Jiří
Language: English
Journal: Aplikace matematiky
ISSN: 0373-6725
Volume: 34
Issue: 5
Year: 1989
Pages: 387-395
Summary lang: English
Summary lang: Russian
Summary lang: Czech
.
Category: math
.
Summary: The periodic autoregressive process with non-vanishing mean and with exogenous variables is investigated in the paper. It is assumed that the model has also periodic variances. The statistical analysis is based on the Bayes approach with a vague prior density. Estimators of the parameters and asymptotic tests of hypotheses are derived. (English)
Keyword: parameter estimation
Keyword: periodic autoregressive process
Keyword: non-vanishing mean
Keyword: exogenous variables
Keyword: periodic variances
Keyword: vague prior density
Keyword: asymptotic tests
Keyword: Bayes approach
Keyword: testing hypotheses
MSC: 62F15
MSC: 62M10
idZBL: Zbl 0697.62084
idMR: MR1014079
DOI: 10.21136/AM.1989.104366
.
Date available: 2008-05-20T18:37:27Z
Last updated: 2020-07-28
Stable URL: http://hdl.handle.net/10338.dmlcz/104366
.
Reference: [1] J. Anděl: Statistical analysis of periodic autoregression.Apl. mat. 28 (1983), 364-385. MR 0712913
Reference: [2] J. Anděl: Periodic autoregression with exogenous variables and equal variances.Proc. 5th Pannonian Symp., 237-245. Akadémiai Kiadó, Budapest 1987. (Eds.: Grossmann, Mogyoródi, Vincze, Wertz.) MR 0956701
Reference: [3] J. Anděl A. Rubio A. Insua: On periodic autoregression with unknown mean.Apl. mat. 30 (1985), 126-139. MR 0778983
Reference: [4] H. J. Newton: Using periodic autoregression for multiple spectral estimation.Technometrics 24 (1982), 109-116. MR 0655574, 10.1080/00401706.1982.10487731
Reference: [5] M. Pagano: On periodic and multiple autoregression.Ann. Statist. 6 (1978), 1310-1317. MR 0523765, 10.1214/aos/1176344376
.

Files

Files Size Format View
AplMat_34-1989-5_5.pdf 1.254Mb application/pdf View/Open
Back to standard record
Partner of
EuDML logo