On unequally spaced AR(1) process

Jan Šindelář; Jiří Knížek

Kybernetika (2003)

  • Volume: 39, Issue: 1, page [13]-27
  • ISSN: 0023-5954

Abstract

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Discrete autoregressive process of the first order is considered. The process is observed at unequally spaced time instants. Both least squares estimate and maximum likelihood estimate of the autocorrelation coefficient are analyzed. We show some dangers related with the estimates when the true value of the autocorrelation coefficient is small. Monte-Carlo method is used to illustrate the problems.

How to cite

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Šindelář, Jan, and Knížek, Jiří. "On unequally spaced AR(1) process." Kybernetika 39.1 (2003): [13]-27. <http://eudml.org/doc/33619>.

@article{Šindelář2003,
abstract = {Discrete autoregressive process of the first order is considered. The process is observed at unequally spaced time instants. Both least squares estimate and maximum likelihood estimate of the autocorrelation coefficient are analyzed. We show some dangers related with the estimates when the true value of the autocorrelation coefficient is small. Monte-Carlo method is used to illustrate the problems.},
author = {Šindelář, Jan, Knížek, Jiří},
journal = {Kybernetika},
keywords = {AR(1) process; unequally spaced; autocorrelation coefficient; least squares estimate; maximum likelihood estimate; AR(1) process; unequally spaced; autocorrelation coefficient; least squares estimate; maximum likelihood estimate},
language = {eng},
number = {1},
pages = {[13]-27},
publisher = {Institute of Information Theory and Automation AS CR},
title = {On unequally spaced AR(1) process},
url = {http://eudml.org/doc/33619},
volume = {39},
year = {2003},
}

TY - JOUR
AU - Šindelář, Jan
AU - Knížek, Jiří
TI - On unequally spaced AR(1) process
JO - Kybernetika
PY - 2003
PB - Institute of Information Theory and Automation AS CR
VL - 39
IS - 1
SP - [13]
EP - 27
AB - Discrete autoregressive process of the first order is considered. The process is observed at unequally spaced time instants. Both least squares estimate and maximum likelihood estimate of the autocorrelation coefficient are analyzed. We show some dangers related with the estimates when the true value of the autocorrelation coefficient is small. Monte-Carlo method is used to illustrate the problems.
LA - eng
KW - AR(1) process; unequally spaced; autocorrelation coefficient; least squares estimate; maximum likelihood estimate; AR(1) process; unequally spaced; autocorrelation coefficient; least squares estimate; maximum likelihood estimate
UR - http://eudml.org/doc/33619
ER -

References

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