Federal Statistical Office
Impact in
- Ecological Modeling top 10%
- Species Distribution and Climate Change
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- Natural Resources and Economic Development
Papers in
-
- Statistical Methods and Inference 11
- Advanced Statistical Methods and Models 7
- Statistical Methods and Bayesian Inference 7
- Top scholars
- Jens WeidmannCarlos Antônio Moreira LeiteC. Scott FindlaySergius L. KuzminJeff E. HoulahanBenedikt R. SchmidtAndrea H. MeyerJürg Ott
- Journals
- Swiss Medical Weekly (6 papers)Journal of the American Statistical Association (5 papers)American Journal of Tropical Medicine and Hygiene (4 papers)Osteoporosis International (4 papers)Electronic Journal of Statistics (3 papers)
- Partner nations
- SwitzerlandUnited StatesGermany
In The Last Decade
Federal Statistical Office
263 papers receiving 7.2k citations
Peers
Comparison fields: 5 of 224
- Ecological Modeling 437
- General Economics, Econometrics and Finance 546
- Statistics and Probability 465
- Global and Planetary Change 1.1k
- Development 168
Countries citing scholars working at Federal Statistical Office
This map shows the geographic impact of research produced by authors working at Federal Statistical Office. 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 papers produced at Federal Statistical Office with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Federal Statistical Office more than expected).
Fields of papers published by authors at Federal Statistical Office
This network shows the impact of papers affiliated with Federal Statistical Office at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Federal Statistical Office at the time of their publication.
About Federal Statistical Office
In recent decades, authors affiliated with Federal Statistical Office have published 356 papers, which have received a total of 8.7k indexed citations . Scholars at this organization have produced 23 papers in Statistics and Probability, 7 papers in Development, 9 papers in Geography, Planning and Development, 1 paper in Chemical Health and Safety and 16 papers in Demography on the topics of Statistical Methods and Inference (11 papers), Geographic Information Systems Studies (8 papers), Advanced Statistical Methods and Models (7 papers), Statistical Methods and Bayesian Inference (7 papers), Energy, Environment, Economic Growth (6 papers), Regional Socio-Economic Development Trends (6 papers), Global Health Care Issues (6 papers) and Chemical Synthesis and Analysis (6 papers). Their work is cited by papers focused on Ecological Modeling (437 citations), General Economics, Econometrics and Finance (546 citations), Statistics and Probability (465 citations), Global and Planetary Change (1.1k citations) and Development (168 citations). Authors at Federal Statistical Office collaborate with scholars in Switzerland, United States and Germany and have published in prestigious journals including Swiss Medical Weekly, Journal of the American Statistical Association, American Journal of Tropical Medicine and Hygiene, Osteoporosis International and Electronic Journal of Statistics. Some of Federal Statistical Office's most productive authors include Jens Weidmann, Carlos Antônio Moreira Leite, C. Scott Findlay, Sergius L. Kuzmin, Jeff E. Houlahan, Benedikt R. Schmidt, Andrea H. Meyer, Jürg Ott, Peter Bühlmann and Carsten Stahmer.
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.