Asymptotic behavior of the Laplacian quasi-maximum likelihood estimator of a ne causal processes

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DC Field	Value	Language
dc.contributor.author	YAKOUB, BOULAROUK	-
dc.date.accessioned	2022-06-19T13:01:38Z	-
dc.date.available	2022-06-19T13:01:38Z	-
dc.date.issued	2016-01-08	-
dc.identifier.uri	http://dspace.centre-univ-mila.dz/jspui/handle/123456789/1772	-
dc.description.abstract	AbstractWe prove the consistency and asymptotic normality of the Laplacian Quasi-Maximum Likelihood Estimator (QMLE) for a general class of causal time series including ARMA, AR(1), GARCH, ARCH(1), ARMA-GARCH, APARCH, ARMA-APARCH,..., processes. We notably exhibit the advantages (moment order and robustness) of this estimator compared to the classical Gaussian QMLE. Numerical simulations con rms the accuracy of this estimator.	en_US
dc.language.iso	en	en_US
dc.publisher	university center of abdalhafid boussouf - MILA	en_US
dc.subject	Laplacian Quasi-Maximum Likelihood Estimator, Strong consistency, Asymptotic normality, ARMA- ARCH processes.	en_US
dc.title	Asymptotic behavior of the Laplacian quasi-maximum likelihood estimator of a ne causal processes	en_US
dc.type	Article	en_US
Appears in Collections:	Mathematics and Computer Science

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