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

Yonghui Liu, Guohua Mao, VICTOR ELISEO LEIVA SANCHEZ, Shuangzhe Liu, Alejandra Tapia

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


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.

Original languageEnglish
Article number693
Issue number5
StatePublished - 1 May 2020
Externally publishedYes


  • AR models
  • EM algorithm
  • Local influence method
  • Maximum likelihood estimation


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