Giray Ökten

702 total citations
47 papers, 430 citations indexed

About

Giray Ökten is a scholar working on Numerical Analysis, Statistics, Probability and Uncertainty and Finance. According to data from OpenAlex, Giray Ökten has authored 47 papers receiving a total of 430 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Numerical Analysis, 24 papers in Statistics, Probability and Uncertainty and 10 papers in Finance. Recurrent topics in Giray Ökten's work include Mathematical Approximation and Integration (29 papers), Probabilistic and Robust Engineering Design (24 papers) and Stochastic processes and financial applications (7 papers). Giray Ökten is often cited by papers focused on Mathematical Approximation and Integration (29 papers), Probabilistic and Robust Engineering Design (24 papers) and Stochastic processes and financial applications (7 papers). Giray Ökten collaborates with scholars based in United States, China and France. Giray Ökten's co-authors include Yaning Liu, Ahmet Göncü, M. Yousuff Hussaini, Murat Tiryakioğlu, Chandra R. Bhat, Bruno Tuffin, Aruna Sivakumar, Scott L. Goodrick, Michael Gnewuch and Bahri Uzunoğlu and has published in prestigious journals such as Materials Science and Engineering A, Journal of Materials Science and Reliability Engineering & System Safety.

In The Last Decade

Giray Ökten

44 papers receiving 401 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Giray Ökten United States 12 156 146 56 54 50 47 430
L. Kocis Australia 3 79 0.5× 69 0.5× 45 0.8× 11 0.2× 12 0.2× 6 436
Ruixue Liu China 9 79 0.5× 54 0.4× 24 0.4× 25 0.5× 99 2.0× 24 435
Agnès Lagnoux France 10 313 2.0× 15 0.1× 79 1.4× 11 0.2× 75 1.5× 21 485
Takashi Goda Japan 11 76 0.5× 131 0.9× 42 0.8× 6 0.1× 20 0.4× 61 341
G. E. Archer United Kingdom 6 211 1.4× 12 0.1× 44 0.8× 8 0.1× 28 0.6× 6 550
Daniel Cárdenas-Morales Spain 9 22 0.1× 232 1.6× 33 0.6× 9 0.2× 298 6.0× 29 533
Pedro Garrancho Spain 10 22 0.1× 235 1.6× 30 0.5× 9 0.2× 297 5.9× 19 528
A. Fraguela Mexico 6 22 0.1× 19 0.1× 27 0.5× 9 0.2× 23 0.5× 17 323
G. K. Kamenev Russia 9 33 0.2× 76 0.5× 177 3.2× 5 0.1× 4 0.1× 32 554
Célestin C. Kokonendji France 17 85 0.5× 12 0.1× 14 0.3× 92 1.7× 672 13.4× 86 1.0k

Countries citing papers authored by Giray Ökten

Since Specialization
Citations

This map shows the geographic impact of Giray Ökten's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Giray Ökten with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giray Ökten more than expected).

Fields of papers citing papers by Giray Ökten

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Giray Ökten. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Giray Ökten. The network helps show where Giray Ökten may publish in the future.

Co-authorship network of co-authors of Giray Ökten

This figure shows the co-authorship network connecting the top 25 collaborators of Giray Ökten. A scholar is included among the top collaborators of Giray Ökten based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Giray Ökten. Giray Ökten is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ökten, Giray, et al.. (2024). DERIVATIVE-BASED SHAPLEY VALUE FOR GLOBAL SENSITIVITY ANALYSIS AND MACHINE LEARNING EXPLAINABILITY. International Journal for Uncertainty Quantification. 15(1). 1–16.
2.
Ökten, Giray, et al.. (2022). Monte Carlo and quasi-Monte Carlo methods for Dempster's rule of combination. International Journal of Approximate Reasoning. 145. 163–186. 2 indexed citations
3.
Ökten, Giray & Yaning Liu. (2021). Randomized quasi-Monte Carlo methods in global sensitivity analysis. Reliability Engineering & System Safety. 210. 107520–107520. 53 indexed citations
4.
Ökten, Giray, et al.. (2020). Implementing de-biased estimators using mixed sequences. Monte Carlo Methods and Applications. 26(4). 293–301. 1 indexed citations
5.
Ökten, Giray, et al.. (2019). Global Sensitivity Analysis for Power Systems via Quasi-Monte Carlo Methods. 446–451. 4 indexed citations
6.
Yuan, Wei, Ahmet Göncü, & Giray Ökten. (2015). Estimating sensitivities of temperature-based weather derivatives. Applied Economics. 47(19). 1942–1955. 4 indexed citations
7.
Göncü, Ahmet & Giray Ökten. (2013). Efficient simulation of a multi-factor stochastic volatility model. Journal of Computational and Applied Mathematics. 259. 329–335. 2 indexed citations
8.
Liu, Yaning, M. Yousuff Hussaini, & Giray Ökten. (2013). Optimization of a Monte Carlo variance reduction method based on sensitivity derivatives. Applied Numerical Mathematics. 72. 160–171. 8 indexed citations
9.
Göncü, Ahmet & Giray Ökten. (2013). Uniform point sets and the collision test. Journal of Computational and Applied Mathematics. 259. 798–804. 6 indexed citations
10.
Ökten, Giray & Ahmet Göncü. (2010). Generating low-discrepancy sequences from the normal distribution: Box–Muller or inverse transform?. Mathematical and Computer Modelling. 53(5-6). 1268–1281. 29 indexed citations
11.
Ökten, Giray, et al.. (2010). Parameterization based on randomized quasi-Monte Carlo methods. Parallel Computing. 36(7). 415–422. 7 indexed citations
12.
Gisser, Micha, James E. McClure, Giray Ökten, & G.J. Santoni. (2009). Some Anomalies Arising from Bandwagons that Impart Upward Sloping Segments to Market Demand. Econ journal watch. 6(1). 21–34. 3 indexed citations
13.
Tiryakioğlu, Murat, et al.. (2009). On evaluating fit of the Lifshitz–Slyozov–Wagner (LSW) distribution to particle size data. Materials Science and Engineering A. 527(6). 1636–1639. 6 indexed citations
14.
Ökten, Giray. (2008). Generalized von Neumann–Kakutani transformation and random-start scrambled Halton sequences. Journal of Complexity. 25(4). 318–331. 15 indexed citations
15.
Ökten, Giray, et al.. (2008). Parameterization based on randomized quasi-Monte Carlo methods. Proceedings - IEEE International Parallel and Distributed Processing Symposium. 26. 1–7. 1 indexed citations
16.
Ökten, Giray, et al.. (2006). A central limit theorem and improved error bounds for a hybrid-Monte Carlo sequence with applications in computational finance. Journal of Complexity. 22(4). 435–458. 27 indexed citations
17.
Ökten, Giray, et al.. (2006). Computation of the endogenous mortgage rates with randomized quasi-Monte Carlo simulations. Mathematical and Computer Modelling. 46(3-4). 459–481. 4 indexed citations
18.
Ökten, Giray. (2005). Solving Linear Equations by Monte Carlo Simulation. SIAM Journal on Scientific Computing. 27(2). 511–531. 8 indexed citations
19.
Sivakumar, Aruna, Chandra R. Bhat, & Giray Ökten. (2005). Simulation Estimation of Mixed Discrete Choice Models with the Use of Randomized Quasi-Monte Carlo Sequences: A Comparative Study. Transportation Research Record Journal of the Transportation Research Board. 1921. 112–122. 19 indexed citations
20.
Ökten, Giray. (2003). Random sampling from low discrepancy sequences: Applications to option pricing. Quality Engineering. 48(5). 501–502. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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