On interpolation in periodic autoregressive processes

Jiří Anděl; Asunción Rubio

Aplikace matematiky (1986)

  • Volume: 31, Issue: 6, page 480-485
  • ISSN: 0862-7940

Abstract

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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.

How to cite

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Anděl, Jiří, and Rubio, Asunción. "On interpolation in periodic autoregressive processes." Aplikace matematiky 31.6 (1986): 480-485. <http://eudml.org/doc/15471>.

@article{Anděl1986,
abstract = {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.},
author = {Anděl, Jiří, Rubio, Asunción},
journal = {Aplikace matematiky},
keywords = {covariance function; multivariate AR(1) process; Hilbert space projections; periodic autoregressive processes; seasonal time series; interpolation; covariance function; multivariate AR(1) process; Hilbert space projections; periodic autoregressive processes; seasonal time series; interpolation},
language = {eng},
number = {6},
pages = {480-485},
publisher = {Institute of Mathematics, Academy of Sciences of the Czech Republic},
title = {On interpolation in periodic autoregressive processes},
url = {http://eudml.org/doc/15471},
volume = {31},
year = {1986},
}

TY - JOUR
AU - Anděl, Jiří
AU - Rubio, Asunción
TI - On interpolation in periodic autoregressive processes
JO - Aplikace matematiky
PY - 1986
PB - Institute of Mathematics, Academy of Sciences of the Czech Republic
VL - 31
IS - 6
SP - 480
EP - 485
AB - 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.
LA - eng
KW - covariance function; multivariate AR(1) process; Hilbert space projections; periodic autoregressive processes; seasonal time series; interpolation; covariance function; multivariate AR(1) process; Hilbert space projections; periodic autoregressive processes; seasonal time series; interpolation
UR - http://eudml.org/doc/15471
ER -

References

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  1. J. Anděl, On interpolation of multiple autoregressive processes, Contributions to Statistics (Jaroslav Hájek Memorial Volume), 13-17, Academia, Prague 1979. (1979) MR0561253
  2. J. Anděl, Statistical analysis of periodic autoregression, Apl. mat. 28 (1983), 364-385. (1983) MR0712913
  3. J. Anděl A. Rubio A. Insua, On periodic autoregression with unknown mean, Apl. mat. 30 (1985), 126-139. (1985) Zbl0585.62152MR0778983
  4. D. G. Luenberger, Optimization by Vector Space Methods, Wiley, New York 1969. (1969) Zbl0176.12701MR0238472
  5. H. Neudecker, 10.1080/01621459.1969.10501027, J. Amer. Statist. Assoc. 64 (1969), 953 - 963. (1969) Zbl0179.33102DOI10.1080/01621459.1969.10501027
  6. M. Pagano, 10.1214/aos/1176344376, Ann. Statist. 6 (1978), 1310-1317. (1978) Zbl0392.62073MR0523765DOI10.1214/aos/1176344376

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