2020
DOI: 10.1007/s00184-020-00774-2
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Conditional maximum Lq-likelihood estimation for regression model with autoregressive error terms

Abstract: In this article, we consider the parameter estimation of regression model with p th order autoregressive (AR(p)) error term. We use the Maximum Lq-likelihood (MLq) estimation method that is proposed by Ferrari and Yang (2010a), as a robust alternative to the classical maximum likelihood (ML) estimation method to handle the outliers in the data. After exploring the MLq estimators for the parameters of interest, we provide some asymptotic properties of the resulting MLq estimators. We give a simulation study and… Show more

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Cited by 3 publications
(1 citation statement)
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“…In (2020), Tuaç et al proposed an autoregressive regression procedure based on the skew-normal and skew-t distributions. Güney et al (2020a) considered the conditional maximum Lq-likelihood (CMLq) estimation method for the autoregressive error terms regression models under normality assumption.…”
Section: Introductionmentioning
confidence: 99%
“…In (2020), Tuaç et al proposed an autoregressive regression procedure based on the skew-normal and skew-t distributions. Güney et al (2020a) considered the conditional maximum Lq-likelihood (CMLq) estimation method for the autoregressive error terms regression models under normality assumption.…”
Section: Introductionmentioning
confidence: 99%