Yerlikaya Özkurt, Fatma

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Yerlikaya-Özkurt,F.
F., Yerlikaya Ozkurt
Y.,Fatma
Y., Fatma
Yerlikaya Özkurt,F.
Fatma Yerlikaya Özkurt
Yerlikaya Ozkurt,Fatma
Yerlikaya Ozkurt,F.
F., Yerlikaya Özkurt
Yerlikaya Ozkurt, Fatma
Fatma, Yerlikaya Özkurt
F.,Yerlikaya Özkurt
Y.Ö.Fatma
F.,Yerlikaya Ozkurt
Fatma, Yerlikaya Ozkurt
Y. Ö. Fatma
Y. O. Fatma
Yerlikaya Özkurt, Fatma
Yerlikaya-Ozkurt, Fatma
Yerlikaya-Ozkurt, Fatma
Yerlikaya-oezkurt, Fatma
Yerlikaya-Ozkurt,F.
Özkurt, Fatma Yerlikaya
Ozkurt, F. Yerlikaya
Job Title
Doktor Öğretim Üyesi
Email Address
fatma.yerlikaya@atilim.edu.tr
Main Affiliation
Industrial Engineering
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Scholarly Output

18

Articles

14

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109/541

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2

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WoS Citation Count

64

Scopus Citation Count

67

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5

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3.56

Scopus Citations per Publication

3.72

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10

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Natural Hazards2
Journal of Applied Statistics2
Journal of Industrial and Management Optimization2
Journal of Dynamics and Games1
Journal of Statistics and Management Systems1
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  • Article
    Citation - WoS: 2
    Citation - Scopus: 2
    Estimation in the Partially Nonlinear Model by Continuous Optimization
    (Taylor & Francis Ltd, 2021) Yerlikaya-Ozkurt, Fatma; Taylan, Pakize; Tez, Mujgan
    A useful model for data analysis is the partially nonlinear model where response variable is represented as the sum of a nonparametric and a parametric component. In this study, we propose a new procedure for estimating the parameters in the partially nonlinear models. Therefore, we consider penalized profile nonlinear least square problem where nonparametric components are expressed as a B-spline basis function, and then estimation problem is expressed in terms of conic quadratic programming which is a continuous optimization problem and solved interior point method. An application study is conducted to evaluate the performance of the proposed method by considering some well-known performance measures. The results are compared against parametric nonlinear model.