Thomas A. Severini

2.8k citations
87 papers · 1.9k · h-index 21

Impact in

Papers in

    • Statistical Methods and Inference 31
    • Statistical Methods and Bayesian Inference 27
    • Advanced Statistical Methods and Models 22
    • Statistical Distribution Estimation and Applications 15
    • Bayesian Methods and Mixture Models 18

Thomas A. Severini

80 papers receiving 1.7k citations

Peers

Thomas A. Severini
Comparison fields: 5 of 154
  • Statistics and Probability 1.3k
  • Statistics, Probability and Uncertainty 206
  • Finance 161
  • General Economics, Econometrics and Finance 112
  • Economics and Econometrics 304
Replace Juan Romo with:
Juan Romo Spain
Yanyuan Ma United States
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Citations per field
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Citations per year

Countries citing papers authored by Thomas A. Severini

Since Specialization
Citations

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

Fields of papers citing papers by Thomas A. Severini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas A. Severini. 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 Thomas A. Severini. The network helps show where Thomas A. Severini may publish in the future.

Co-authors

The 24 scholars most cited alongside Thomas A. Severini, 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 Thomas A. Severini Line = papers co-authored together Thomas A. Severini links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2000359
2 1994263
3 1992226
4 199867
5 199464
6 200563
7 199862
8 199357
9 199147
10 201745
11 199843
12 200739
13 199939
14 199138
15 200135
16 199134
17
On the relationship between Bayesian and non-Bayesian elimination of nuisance parameters
199932
18 200628
19 200225
20 200524

About Thomas A. Severini

Thomas A. Severini is a scholar working on Statistics and Probability, Artificial Intelligence, Statistics, Probability and Uncertainty, Economics and Econometrics and General Economics, Econometrics and Finance, having authored 87 papers that have together received 1.9k indexed citations. Recurring topics across this work include Statistical Methods and Inference (31 papers), Statistical Methods and Bayesian Inference (27 papers), Advanced Statistical Methods and Models (22 papers), Bayesian Methods and Mixture Models (18 papers), Statistical Distribution Estimation and Applications (15 papers), Advanced Statistical Process Monitoring (8 papers), Monetary Policy and Economic Impact (6 papers) and Probabilistic and Robust Engineering Design (4 papers). The work is most often cited by research in Statistics and Probability (1.3k citations), Statistics, Probability and Uncertainty (206 citations), Finance (161 citations), General Economics, Econometrics and Finance (112 citations) and Economics and Econometrics (304 citations). Thomas A. Severini has collaborated with scholars based in United States, Luxembourg and Philippines. Frequent co-authors include Joan G. Staniswalis, Wing Hung Wong, Gautam Tripathi, Daniel B. Hall, Ravi Allada, Nicola Sartori, Jason A. Osborne, Zhenyu Zhao, Jinsong Chen and Ya‐Chen Tina Shih. Their work appears in journals such as Journal of the American Statistical Association, Biometrika, Journal of Econometrics, Journal of the Royal Statistical Society Series B (Statistical Methodology) and The Annals of Statistics.

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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