On periodic autoregression with unknown mean

Jiří Anděl; Asunción Rubio; Antonio Insua

Aplikace matematiky (1985)

  • Volume: 30, Issue: 2, page 126-139
  • ISSN: 0862-7940

Abstract

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If the parameters of an autoregressive model are periodic functions we get a periodic autoregression. In the paper the case is investigated when the expectation can also be a periodic function. The innovations have either constant or periodically changing variances.

How to cite

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Anděl, Jiří, Rubio, Asunción, and Insua, Antonio. "On periodic autoregression with unknown mean." Aplikace matematiky 30.2 (1985): 126-139. <http://eudml.org/doc/15390>.

@article{Anděl1985,
abstract = {If the parameters of an autoregressive model are periodic functions we get a periodic autoregression. In the paper the case is investigated when the expectation can also be a periodic function. The innovations have either constant or periodically changing variances.},
author = {Anděl, Jiří, Rubio, Asunción, Insua, Antonio},
journal = {Aplikace matematiky},
keywords = {estimating parameters; testing hypotheses; Periodic autoregressive models; time-varying coefficients; Gaussian white noise; unknown mean; innovation; seasonal series; Gaussian maximum likelihood methods; estimating parameters; testing hypotheses; Periodic autoregressive models; time-varying coefficients; Gaussian white noise; unknown mean; innovation; seasonal series; Gaussian maximum likelihood methods},
language = {eng},
number = {2},
pages = {126-139},
publisher = {Institute of Mathematics, Academy of Sciences of the Czech Republic},
title = {On periodic autoregression with unknown mean},
url = {http://eudml.org/doc/15390},
volume = {30},
year = {1985},
}

TY - JOUR
AU - Anděl, Jiří
AU - Rubio, Asunción
AU - Insua, Antonio
TI - On periodic autoregression with unknown mean
JO - Aplikace matematiky
PY - 1985
PB - Institute of Mathematics, Academy of Sciences of the Czech Republic
VL - 30
IS - 2
SP - 126
EP - 139
AB - If the parameters of an autoregressive model are periodic functions we get a periodic autoregression. In the paper the case is investigated when the expectation can also be a periodic function. The innovations have either constant or periodically changing variances.
LA - eng
KW - estimating parameters; testing hypotheses; Periodic autoregressive models; time-varying coefficients; Gaussian white noise; unknown mean; innovation; seasonal series; Gaussian maximum likelihood methods; estimating parameters; testing hypotheses; Periodic autoregressive models; time-varying coefficients; Gaussian white noise; unknown mean; innovation; seasonal series; Gaussian maximum likelihood methods
UR - http://eudml.org/doc/15390
ER -

References

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  1. J. Anděl, Statistical analysis of periodic autoregression, Apl. mat. 28 (1983), 364-365. (1983) MR0712913
  2. G. E. P. Box G. C. Tiao, 10.1080/01621459.1975.10480264, J. Amer. Statist. Assoc. 70 (1975), 70-79. (1975) MR0365957DOI10.1080/01621459.1975.10480264
  3. E. G. Gladyshev, Periodically correlated random sequences, Soviet Math. 2 (1961), 385-388. (1961) Zbl0212.21401
  4. E. G. Gladyshev, Periodically and almost periodically correlated random process with continuous time parameter, Theory Prob. Appl. 8 (1963), 173-177. (1963) 
  5. M. Pagano, 10.1214/aos/1176344376, Ann. Statist. 6 (1978), 1310-1317. (1978) MR0523765DOI10.1214/aos/1176344376
  6. A. Zellner, An introduction to Bayesian Inference in Econometrics, Wiley, New York, 1971. (1971) Zbl0246.62098MR0433791

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