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Title: On interpolation in periodic autoregressive processes (English)
Author: Anděl, Jiří
Author: Rubio, Asunción
Language: English
Journal: Aplikace matematiky
ISSN: 0373-6725
Volume: 31
Issue: 6
Year: 1986
Pages: 480-485
Summary lang: English
Summary lang: Russian
Summary lang: Czech
Category: math
Summary: The periodic autoregressive processes are useful in statistical analysis of seasonal time series. Some procedures (e.g. extrapolation) are quite analogous to those in the clasical autoregressive models. The problem of interpolation needs, however, some special methods. They are demonstrated in the paper on the case of the process of the second order with the period of length 2. (English)
Keyword: covariance function
Keyword: multivariate AR(1) process
Keyword: Hilbert space projections
Keyword: periodic autoregressive processes
Keyword: seasonal time series
Keyword: interpolation
MSC: 62M10
MSC: 62M20
idZBL: Zbl 0622.62088
idMR: MR0870483
DOI: 10.21136/AM.1986.104225
Date available: 2008-05-20T18:31:11Z
Last updated: 2020-07-28
Stable URL:
Reference: [1] J. Anděl: On interpolation of multiple autoregressive processes.Contributions to Statistics (Jaroslav Hájek Memorial Volume), 13-17, Academia, Prague 1979. MR 0561253
Reference: [2] J. Anděl: Statistical analysis of periodic autoregression.Apl. mat. 28 (1983), 364-385. MR 0712913
Reference: [3] J. Anděl A. Rubio A. Insua: On periodic autoregression with unknown mean.Apl. mat. 30 (1985), 126-139. MR 0778983
Reference: [4] D. G. Luenberger: Optimization by Vector Space Methods.Wiley, New York 1969. Zbl 0176.12701, MR 0238472
Reference: [5] H. Neudecker: Some theorems on matrix differentiation with special reference to Kronecker matrix products.J. Amer. Statist. Assoc. 64 (1969), 953 - 963. Zbl 0179.33102, 10.1080/01621459.1969.10501027
Reference: [6] M. Pagano: On periodic and multiple autoregression.Ann. Statist. 6 (1978), 1310-1317. MR 0523765, 10.1214/aos/1176344376


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