Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/11078

TitleAsymptotic and pre-asymptotic tail behavior of a power max-autoregressive model
Author(s)Ferreira, Marta Susana
Castro, Luisa Canto e
KeywordsMarkov Chains
Extreme value theory
Dependence conditions
Auto-asymptotic-tail-dependence function
Tail index
Extremal index
Issue date2010
PublisherProbstat Forum
JournalProbstat Forum
CitationFERREIRA, Marta; CASTRO, Luisa Canto e - Asymptotic and pre-asymptotic tail behavior of a power max-autoregressive model. "ProbStat Forum" [Em linha]. 3:08 (2010) 91-107. [Consult. 17 Nov. 2010]. Disponível em : http://probstat.org.in/PSF-0610.pdf. ISSN 0974-3235.
Abstract(s)Max-autoregressive models for time series data are useful when we want to make inference about rare events, mainly in areas like hydrology, geophysics and finance. Here we present a power max-autoregressive ($p$ARMAX) process, $\{X_i\}$, defined in such a way that the asymptotic tail dependence coefficient of Ledford and Tawn, computed for observations lag $m$ apart ($\eta_m$), exhibits a power decay with $m$ for larger values of $c$, the main parameter of the process, namely, $\eta_m=c^m$, $c\in(1/2,1)$. We also look at the threshold-dependent form of the extremal index, which is an important functional when extending discussions of extreme values from independent and identically distributed (i.i.d.) sequences to stationary ones. We state an approach for this functional as well as its connection with the coefficient $\eta$ for the $p$ARMAX process.
TypeArticle
URIhttp://hdl.handle.net/1822/11078
ISSN0974-3235
Publisher versionhttp://probstat.org.in/
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CMAT - Artigos em revistas com arbitragem / Papers in peer review journals

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