Seiji Nabeya

698 citations
28 papers · 414 indexed · h-index 12
Topics
Financial Risk and Volatility Modeling (10 papers)Statistical Methods and Inference (7 papers)Bayesian Methods and Mixture Models (5 papers)
Partner nations
JapanUnited StatesCanada

In The Last Decade

Seiji Nabeya

28 papers receiving 376 citations

Peers

Seiji Nabeya
Comparison fields: 5 of 48
  • Finance 204
  • General Economics, Econometrics and Finance 167
  • Statistics and Probability 163
  • Economics and Econometrics 142
  • Applied Mathematics 50
Replace Norbert Herrndorf with:
Norbert Herrndorf Germany
Erich Haeusler Germany
David John Scott Australia
Estáte V. Khmaladze New Zealand
Ken-ichi Yoshihara Japan
Tai‐Ho Wang United States
A. P. J. Abrahamse Bolivia
Peter Jäckel Germany
Tuan D. Pham United States
Alfredas Račkauskas Lithuania
Seiji Nabeya relative to Norbert Herrndorf Germany Norbert Herrndorf's profile →
Citations per field
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Norbert Herrndorf · 1×
Citations per year

Countries citing papers authored by Seiji Nabeya

Since Specialization
Citations

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

Fields of papers citing papers by Seiji Nabeya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seiji Nabeya

This figure shows the co-authorship network connecting the top 25 collaborators of Seiji Nabeya. A scholar is included among the top collaborators of Seiji Nabeya 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 Seiji Nabeya. Seiji Nabeya 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
#WorkIndexed citations
1
Statistical Analysis of Baseball Data
1
2 7
3 6
4 6
5 14
6 1
7 29
8 2
9 2
10
Application of the theory of integral equations to the derivation of asymptotic distributions in time series analysis
5
11 1
12 1
13 8
14 3
15 1
16 11
17 15
18 21
19 16
20 25

About Seiji Nabeya

Seiji Nabeya is a scholar working on Statistics and Probability, Finance and General Economics, Econometrics and Finance, having authored 28 papers that have together received 414 indexed citations. Recurring topics across this work include Financial Risk and Volatility Modeling (10 papers), Statistical Methods and Inference (7 papers) and Bayesian Methods and Mixture Models (5 papers). The work is most often cited by research in Finance (204 citations), General Economics, Econometrics and Finance (167 citations) and Statistics and Probability (163 citations). Seiji Nabeya has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Katsuto Tanaka, Pierre Perrón, Bent E. Sørensen, Kjell A. Doksum, Takeaki Kariya, Eiji Yamamoto and Kazumasa Wakimoto. Their work appears in journals such as Econometrica, Biometrika and Journal of Econometrics.

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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