Zobrazeno 1 - 10
of 47
pro vyhledávání: '"L. Kavalieris"'
Publikováno v:
Journal of Time Series Analysis. 24:165-172
Two multistage methods for estimating scalar ARMA models are investigated. Both estimate innovations using an autoregression; these are used to obtain initial ARMA parameter estimates by regression and finally the initial estimates are refined by gen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7329d1f0f23915a2bed29ce53e1e5308
https://doi.org/10.1111/1467-9892.00301
https://doi.org/10.1111/1467-9892.00301
Publikováno v:
Geocarto International. 14:29-34
This study examined the temporal variability of sea surface temperature (SST) of three water masses east of the South Island, New Zealand, where two of these water masses are part of the global Subtropical Front (STF). The STF is well defined and can
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b77da561e57ae8c3d4082eff5a4de98f
https://doi.org/10.1080/10106049908542114
https://doi.org/10.1080/10106049908542114
Autor:
E. J. Hannan, L. Kavalieris
Publikováno v:
Australian Journal of Statistics. 37:105-110
Summary This paper considers the relationship between ARMA parameterisations of models for y(t) and Ay(t), where A is invertible and y(t) is a vector time series (t = 0,±1,…). An ARMA model for the transformed series Ay(t) may have fewer parameter
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::916918b5996dbfbc5efb666ac8e876a5
https://doi.org/10.1111/j.1467-842x.1995.tb00876.x
https://doi.org/10.1111/j.1467-842x.1995.tb00876.x
Autor:
E. J. Hannan, L. Kavalieris
Publikováno v:
Journal of Time Series Analysis. 15:613-625
We consider the estimation of the number of sinusoidal terms in a time series contaminated by additive noise with unknown correlation structure. The method fits sinusoidal terms by least squares and models the noise component using a high order autor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9ca3e83aa44574ab24c791ad4444265d
https://doi.org/10.1111/j.1467-9892.1994.tb00216.x
https://doi.org/10.1111/j.1467-9892.1994.tb00216.x
Autor:
L. Kavalieris
Publikováno v:
Journal of Time Series Analysis. 14:485-496
We discuss the problem of estimating the transfer function and an autoregressive model for measurement noise in a linear system. A parameterization that is often more parsimonious than the usual ARX model is used. Particular emphasis is given to the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b7594d2b16599e27a3917be20d8d095
https://doi.org/10.1111/j.1467-9892.1993.tb00159.x
https://doi.org/10.1111/j.1467-9892.1993.tb00159.x
Publikováno v:
Journal of Applied Phycology. 4:357-369
Tissue samples ofMacrocystis pyrifera from 2 sites in southern New Zealand and harvested over a period of 12 months were analysed for alginate content and composition (M:G ratio). Plants were divided into three frond classes of different length and e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::38d3434836526aba4a1007154561a192
https://doi.org/10.1007/bf02185794
https://doi.org/10.1007/bf02185794
Akademický článek
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Autor:
L. Kavalieris
Publikováno v:
Biometrika. 78:920-922
SUMMARY A method for the estimation of parameters and model orders in an autoregressive-moving average system was introduced by Hannan & Rissanen (1982). That method may overestimate the model orders. Here an information theoretic order estimation pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dd7a1c74f77477875312b7cb1cd00b5d
https://doi.org/10.1093/biomet/78.4.920
https://doi.org/10.1093/biomet/78.4.920
Publikováno v:
Biometrika. 73:119-133
On compare par simulation deux algorithmes bien connus avec une methode liee a l'algorithme de Hannan et Rissanen (1982)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f823ad3f11b8539dd993fc22439a251a
https://doi.org/10.1093/biomet/73.1.119
https://doi.org/10.1093/biomet/73.1.119
Autor:
L. Kavalieris
Publikováno v:
Journal of Time Series Analysis. 10:271-281
Several criteria for the estimation of the order of an autoregressive representation of a stationary time series are examined. There need not be a true finite-order autoregression model for the data, so that the purpose of model identification is to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1661cfc2456296395deab238a6361f5
https://doi.org/10.1111/j.1467-9892.1989.tb00028.x
https://doi.org/10.1111/j.1467-9892.1989.tb00028.x