Ayşen Akkaya

E-mail

akkay@metu.edu.tr

Department

Department of Statistics

ORCID

0000-0002-0886-3295

Scopus Author ID

6603740998

Web of Science Researcher ID

W-7848-2018

Adaptive estimation of autoregression models under long-tailed symmetric distribution Yentür, Begüm; Akkaya, Ayşen; Bayrak, Özlem Türker (2022-01-01) © 2022 Taylor & Francis Group, LLC.Non-normal innovations in autoregression models frequently occur in practice. In this situation, least squares (LS) estimators are known to be inefficient and non-robust, and maximum like...
Re: Ratio of umbilical and cerebral artery pulsatility indices in assessment of fetal risk: numerator and denominator matter Kalafat, E.; Ozturk, E.; Kalaylioglu, Z.; Akkaya, Ayşen; Khalil, A. (Wiley, 2020-08-01)
Estimation of AR(1) Model Having Generalized Logistic Disturbances Akkaya, Ayşen (null; 2020-01-02) 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...
Adaptive estimation of autoregressive models under long-tailed symmetric distribution Yentür, Begüm; Bayrak, Özlem Türker; Akkaya, Ayşen (2019-07-08) In this paper, we consider the autoregressive models where the error term is non-normal; specifically belongs to a long-tailed symmetric distribution family since it is more relevant in practice than the normal distributio...
Inference of Autoregressive Model with Stochastic Exogenous Variable Under Short-Tailed Symmetric Distributions Bayrak, Ozlem Tuker; Akkaya, Ayşen (2018-12-01) In classical autoregressive models, it is assumed that the disturbances are normally distributed and the exogenous variable is non-stochastic. However, in practice, short-tailed symmetric disturbances occur frequently and ...
A New Estimation Technique for AR(1) Model with Long-tailed Symmetric Innovations Akkaya, Ayşen (null; 2017-09-17) In recent years, it is seen in many time series applications that innovations are non-normal. In this situation, it is known that the least squares (LS) estimators are neither efficient nor robust and maximum likelihood (M...
ROBUST AND BAYESIAN PARAMETER ESTIMATION IN TIME DEPENDENT SEISMIC HAZARD ANALYSIS Altay, Umut; Akkaya, Ayşen; Yucemen, M Semih (null; 2017-08-06)
Modelling Spatial Correlation for the Evaluation of Network System Reliability Akkaya, Ayşen; Altay, Umut (2017-05-08) Lifeline network systems extend spatially over large geographical regions. Such network systems are composed of interconnected components most of which can be idealized as long segments. Correlation resulting from similar ...
A Comparative Study of Stochastic Models for Seismic Hazard Estimation Akkaya, Ayşen (null, 2016-01-01)
Robust pairwise multiple comparisons under short-tailed symmetric distributions Balci, Sibel; Akkaya, Ayşen (2015-11-02) In one-way ANOVA, most of the pairwise multiple comparison procedures depend on normality assumption of errors. In practice, errors have non-normal distributions so frequently. Therefore, it is very important to develop ro...

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