Pakize Taylan

18 papers receiving 382 citations

Peers

Pakize Taylan
Comparison fields: 5 of 90
  • Statistics and Probability 64
  • Management Science and Operations Research 70
  • Statistics, Probability and Uncertainty 26
  • Computational Theory and Mathematics 52
  • Modeling and Simulation 15
Replace Nicolas Langrené with:
Nicolas Langrené Australia
J. S. Dagpunar United Kingdom
Michael Z. Zgurovsky Ukraine
Md Sadikur Rahman India
Pavlo Krokhmal United States
George B. Kleindorfer United States
J. W. Cohen United States
Deepak Singh India
Pakize Taylan relative to Nicolas Langrené Australia Nicolas Langrené's profile →
Citations per field
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Nicolas Langrené · 1×
Citations per year

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-authors

The 10 scholars most cited alongside Pakize Taylan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Pakize Taylan Line = papers co-authored together Pakize Taylan links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2011122
2 200761
3 201045
4 201030
5 200826
6 200822
7 200821
8 202017
9 201015
10
NEW APPROACHES TO REGRESSION IN FINANCIAL MATHEMATICS BY ADDITIVE MODELS
200710
11 20149
12 20197
13 20086
14 20103
15 20241
16 20191
17 20201
18 20181
19 20240

About Pakize Taylan

Pakize Taylan is a scholar working on Statistics and Probability, Control and Systems Engineering, Applied Mathematics, Molecular Biology and Numerical Analysis, having authored 19 papers that have together received 398 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (9 papers), Statistical Methods and Inference (6 papers), Statistical and numerical algorithms (5 papers), Control Systems and Identification (4 papers), Bioinformatics and Genomic Networks (3 papers), Sparse and Compressive Sensing Techniques (3 papers), Gene Regulatory Network Analysis (3 papers) and Advanced Statistical Process Monitoring (2 papers). The work is most often cited by research in Statistics and Probability (64 citations), Management Science and Operations Research (70 citations), Statistics, Probability and Uncertainty (26 citations), Computational Theory and Mathematics (52 citations) and Modeling and Simulation (15 citations). Pakize Taylan has collaborated with scholars based in Türkiye, China and Kazakhstan. Frequent co-authors include Gerhard‐Wilhelm Weber, İnci Batmaz, Gülser Köksal, Amir Beck, Ömür Uğur, Mehmet Serkan Çetin, Sırma Zeynep Alparslan Gök, Pandian Vasant, Nader Barsoum and Ersin Uysal. Their work appears in journals such as Optimization, Top, Discrete Applied Mathematics, Journal of Computational and Applied Mathematics and Inverse Problems in Science and Engineering.

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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