Pakize Taylan

549 total citations
19 papers, 398 citations indexed

About

Pakize Taylan is a scholar working on Statistics and Probability, Control and Systems Engineering and Applied Mathematics. According to data from OpenAlex, Pakize Taylan has authored 19 papers receiving a total of 398 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Statistics and Probability, 5 papers in Control and Systems Engineering and 5 papers in Applied Mathematics. Recurrent topics in Pakize Taylan's work include Advanced Statistical Methods and Models (9 papers), Statistical Methods and Inference (6 papers) and Statistical and numerical algorithms (5 papers). Pakize Taylan is often cited by papers focused on Advanced Statistical Methods and Models (9 papers), Statistical Methods and Inference (6 papers) and Statistical and numerical algorithms (5 papers). Pakize Taylan collaborates with scholars based in Türkiye, China and Russia. Pakize Taylan's co-authors include Gerhard‐Wilhelm Weber, İnci Batmaz, Gülser Köksal, Amir Beck, Ömür Uğur, Sırma Zeynep Alparslan Gök, Mehmet Serkan Çetin, Nader Barsoum, Pandian Vasant and Ersin Uysal and has published in prestigious journals such as Computers & Mathematics with Applications, Journal of Computational and Applied Mathematics and Discrete Applied Mathematics.

In The Last Decade

Pakize Taylan

18 papers receiving 382 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pakize Taylan Türkiye 10 75 70 67 64 52 19 398
Xin Dang United States 11 190 2.5× 69 1.0× 33 0.5× 146 2.3× 55 1.1× 44 462
David E. Kaufman United States 11 65 0.9× 46 0.7× 83 1.2× 33 0.5× 50 1.0× 26 850
Zaven A. Karian United States 11 90 1.2× 60 0.9× 13 0.2× 200 3.1× 23 0.4× 26 464
Ryuhei Miyashiro Japan 12 65 0.9× 184 2.6× 7 0.1× 95 1.5× 35 0.7× 30 447
Martin Newby United Kingdom 16 53 0.7× 63 0.9× 20 0.3× 268 4.2× 26 0.5× 47 768
Jin-Li Guo China 12 32 0.4× 58 0.8× 39 0.6× 25 0.4× 9 0.2× 55 451
Attila Csenki United Kingdom 14 37 0.5× 67 1.0× 18 0.3× 140 2.2× 42 0.8× 55 744
Tomáš Tichý Czechia 11 59 0.8× 176 2.5× 7 0.1× 39 0.6× 56 1.1× 83 502
Nicolas Langrené Australia 12 99 1.3× 71 1.0× 7 0.1× 29 0.5× 16 0.3× 29 462

Countries citing papers authored by Pakize Taylan

Since Specialization
Citations

This map shows the geographic impact of Pakize Taylan'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 Pakize Taylan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pakize Taylan more than expected).

Fields of papers citing papers by Pakize Taylan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pakize Taylan. 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 Pakize Taylan. The network helps show where Pakize Taylan may publish in the future.

Co-authorship network of co-authors of Pakize Taylan

This figure shows the co-authorship network connecting the top 25 collaborators of Pakize Taylan. A scholar is included among the top collaborators of Pakize Taylan 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 Pakize Taylan. Pakize Taylan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Taylan, Pakize, et al.. (2024). Spline based sparseness and smoothness for partially nonlinear model via C-fused Lasso. Journal of Industrial and Management Optimization. 21(2). 1120–1144.
2.
Taylan, Pakize, et al.. (2024). Enhancing classification modeling through feature selection and smoothness: A conic-fused lasso approach integrated with mean shift outlier modelling. Journal of Dynamics and Games. 12(1). 1–23. 1 indexed citations
3.
Taylan, Pakize, et al.. (2020). Estimation in the partially nonlinear model by continuous optimization. Journal of Applied Statistics. 48(13-15). 2826–2846. 1 indexed citations
4.
Taylan, Pakize, et al.. (2020). A new outlier detection method based on convex optimization: application to diagnosis of Parkinson’s disease. Journal of Applied Statistics. 48(13-15). 2421–2440. 17 indexed citations
5.
Taylan, Pakize, et al.. (2019). New computational methods for classification problems in the existence of outliers based on conic quadratic optimization. Communications in Statistics - Simulation and Computation. 49(3). 753–770. 7 indexed citations
6.
Taylan, Pakize, et al.. (2019). A new approach to adaptive spline threshold autoregression by using Tikhonov regularization and continuous optimization. Journal of Statistics and Management Systems. 22(6). 1127–1142. 1 indexed citations
7.
Taylan, Pakize, et al.. (2018). On curvature measurements of the nonlinear errors in variable models by application study. Journal of Statistics and Management Systems. 21(5). 741–765. 1 indexed citations
8.
Taylan, Pakize, et al.. (2014). An approach to the mean shift outlier model by Tikhonov regularization and conic programming. Intelligent Data Analysis. 18(1). 79–94. 9 indexed citations
9.
Weber, Gerhard‐Wilhelm, et al.. (2011). CMARS: a new contribution to nonparametric regression with multivariate adaptive regression splines supported by continuous optimization. Inverse Problems in Science and Engineering. 20(3). 371–400. 122 indexed citations
10.
Taylan, Pakize, et al.. (2010). CMARS and GAM & CQP—Modern optimization methods applied to international credit default prediction. Journal of Computational and Applied Mathematics. 235(16). 4639–4651. 30 indexed citations
11.
Taylan, Pakize, et al.. (2010). On the foundations of parameter estimation for generalized partial linear models with B-splines and continuous optimization. Computers & Mathematics with Applications. 60(1). 134–143. 15 indexed citations
12.
Taylan, Pakize, et al.. (2010). ON FOUNDATIONS OF PARAMETER ESTIMATION FOR GENERALIZED PARTIAL LINEAR MODELS WITH B-SPLINES AND CONTINUOUS OPTIMIZATION. AIP conference proceedings. 297–304. 3 indexed citations
13.
14.
Taylan, Pakize & Gerhard‐Wilhelm Weber. (2008). Organization in Finance Prepared by Stochastic Differential Equations with Additive and Nonlinear Models and Continuous Optimization. Organizacija. 41(5). 185–193. 6 indexed citations
15.
Weber, Gerhard‐Wilhelm, et al.. (2008). On optimization, dynamics and uncertainty: A tutorial for gene-environment networks. Discrete Applied Mathematics. 157(10). 2494–2513. 26 indexed citations
16.
Weber, Gerhard‐Wilhelm, et al.. (2008). Optimization of gene-environment networks in the presence of errors and uncertainty with Chebychev approximation. Top. 16(2). 284–318. 21 indexed citations
17.
Weber, Gerhard‐Wilhelm, et al.. (2008). Mathematical contributions to dynamics and optimization of gene-environment networks. Optimization. 57(2). 353–377. 22 indexed citations
18.
Taylan, Pakize & Gerhard‐Wilhelm Weber. (2007). NEW APPROACHES TO REGRESSION IN FINANCIAL MATHEMATICS BY ADDITIVE MODELS. 12(2). 10 indexed citations
19.
Taylan, Pakize, Gerhard‐Wilhelm Weber, & Amir Beck. (2007). New approaches to regression by generalized additive models and continuous optimization for modern applications in finance, science and technology. Optimization. 56(5-6). 675–698. 61 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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