Estimation of AR(1) Model Having Generalized Logistic Disturbances

Date

2020-01-02

Author

Akkaya, Ayşen

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Non-normality is becoming a common feature in real life applications. Using non-normal disturbances in autoregressive models induces non-linearity in the likelihood equations so that maximum likelihood estimators cannot be derived analytically. Thus, modified maximum likelihood estimation (MMLE) technique is introduced in literature to overcome this difficulty. However, this method assumes the shape parameter to be known which is not realistic in real life. Recently, for unknown shape parameter case, adaptive modified maximum likelihood estimation (AMMLE) method that combines MMLE with Huber estimation method is suggested in literature. In this study, we adopt AMMLE method to AR(1) model where the disturbances are Generalized Logistic distributed. Although Huber M-estimation is not applicable to skew distributions, the AMMLE method extends Huber type work to skew distributions. We derive the estimators and evaluate their performance in terms of effici

Subject Keywords

Adaptive modified maximum likelihood estimation, Maximum likelihood estimation, Least squares, Efficiency, Robustness

URI

http://istkon2019.giresun.edu.tr/Files/ckFiles/istkon2019-giresun-edu-tr/AbstractBook10112019.pdf
https://hdl.handle.net/11511/78976

Conference Name

11. International Statistics Congress- ISC-(4 - 08 Ekim 2019)

Collections

Department of Statistics, Conference / Seminar

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Citation Formats

A. Akkaya, “Estimation of AR(1) Model Having Generalized Logistic Disturbances,” presented at the 11. International Statistics Congress- ISC-(4 - 08 Ekim 2019), Türkiye, 2020, Accessed: 00, 2021. [Online]. Available: http://istkon2019.giresun.edu.tr/Files/ckFiles/istkon2019-giresun-edu-tr/AbstractBook10112019.pdf.