Diagnostic analytics for an autoregressive model under the skew-normal distribution

Liu, Yonghui; Mao, Guohua; Leiva, Víctor; Liu, Shuangzhe; Tapia, Alejandra

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dc.contributor.author	Liu, Yonghui
dc.contributor.author	Mao, Guohua
dc.contributor.author	Leiva, Víctor
dc.contributor.author	Liu, Shuangzhe
dc.contributor.author	Tapia, Alejandra
dc.date.accessioned	2020-11-12T14:52:37Z
dc.date.available	2020-11-12T14:52:37Z
dc.date.issued	2020
dc.identifier.uri	http://repositorio.ucm.cl/handle/ucm/3196
dc.description.abstract	Autoregressive models have played an important role in time series. In this paper, an autoregressive model based on the skew-normal distribution is considered. The estimation of its parameters is carried out by using the expectation–maximization algorithm, whereas the diagnostic analytics are conducted by means of the local influence method. Normal curvatures for the model under four perturbation schemes are established. Simulation studies are conducted to evaluate the performance of the proposed procedure. In addition, an empirical example involving weekly financial return data are analyzed using the procedure with the proposed diagnostic analytics, which has improved the model fit.	es_CL
dc.language.iso	en	es_CL
dc.rights	Atribución-NoComercial-SinDerivadas 3.0 Chile	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/cl/	*
dc.source	Mathematics, 8(5), 693	es_CL
dc.subject	AR models	es_CL
dc.subject	EM algorithm	es_CL
dc.subject	Local influence method	es_CL
dc.subject	Maximum likelihood estimation	es_CL
dc.title	Diagnostic analytics for an autoregressive model under the skew-normal distribution	es_CL
dc.type	Article	es_CL
dc.ucm.facultad	Facultad de Ciencias Básicas	es_CL
dc.ucm.indexacion	Scopus	es_CL
dc.ucm.indexacion	Isi	es_CL
dc.ucm.doi	doi.org/10.3390/math8050693	es_CL