Federal Statistical Office
Impact in
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- Species Distribution and Climate Change
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- Amphibian and Reptile Biology
Papers in
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- Statistical Methods and Inference 7
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- Geographic Information Systems Studies 8
- Top scholars
- C. Scott FindlayJeff E. HoulahanAndrea Hans MeyerBenedikt R. SchmidtSergius L. KuzminJürg OttCarsten StahmerAwudu Abdulai
- Journals
- Swiss Medical Weekly (7 papers)Osteoporosis International (4 papers)Journal of the American Statistical Association (4 papers)Zeitschrift für schweizerische Statistik und Volkswirtschaft/Schweizerische Zeitschrift für Volkswirtschaft und Statistik/Swiss journal of economics and statistics (3 papers)Human Genetics (3 papers)
- Partner nations
- SwitzerlandGermanyUnited States
In The Last Decade
Federal Statistical Office
244 papers receiving 5.6k citations
Peers
Comparison fields: 5 of 221
- Ecological Modeling 432
- Global and Planetary Change 1.1k
- Insect Science 441
- Parasitology 178
- Ecology 683
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 324 papers, which have received a total of 7.1k indexed citations . Scholars at this organization have produced 18 papers in Statistics and Probability, 9 papers in Geography, Planning and Development, 1 paper in Chemical Health and Safety, 5 papers in Development and 2 papers in Equine on the topics of Geographic Information Systems Studies (8 papers), Statistical Methods and Inference (7 papers), Global Health Care Issues (7 papers), Energy, Environment, Economic Growth (6 papers), Chemical Synthesis and Analysis (6 papers), Social Media and Politics (5 papers), Fiscal Policy and Economic Growth (5 papers) and Birth, Development, and Health (5 papers). Their work is cited by papers focused on Ecological Modeling (432 citations), Global and Planetary Change (1.1k citations), Insect Science (441 citations), Parasitology (178 citations) and Ecology (683 citations). Authors at Federal Statistical Office collaborate with scholars in Switzerland, Germany and United States and have published in prestigious journals including Swiss Medical Weekly, Osteoporosis International, Journal of the American Statistical Association, Zeitschrift für schweizerische Statistik und Volkswirtschaft/Schweizerische Zeitschrift für Volkswirtschaft und Statistik/Swiss journal of economics and statistics and Human Genetics. Some of Federal Statistical Office's most productive authors include C. Scott Findlay, Jeff E. Houlahan, Andrea Hans Meyer, Benedikt R. Schmidt, Sergius L. Kuzmin, Jürg Ott, Carsten Stahmer, Awudu Abdulai, Werner A. Stahel and P. Bassetti.
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.