Alexander Kowarik
- Artificial Intelligence top 10%
- Statistics and Probability top 5%
- Sociology and Political Science
- Molecular Biology
- Epidemiology
- Co-authors
- Matthias TemplPeter FilzmoserOlivier DupriezSiegfried KasperAndreas AlfonsRichard FreyDietmar WinklerEdda Pjrek
- Topics
- Data Analysis with R (4 papers)Statistical Methods and Bayesian Inference (3 papers)demographic modeling and climate adaptation (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of Statistical SoftwareComputational Statistics & Data Analysis
- Partner nations
- AustriaSwitzerlandUnited States
In The Last Decade
Alexander Kowarik
15 papers receiving 631 citations
Hit Papers
Peers
Comparison fields: 5 of 159
- Artificial Intelligence 145
- Statistics and Probability 97
- Sociology and Political Science 69
- Molecular Biology 59
- Epidemiology 56
Countries citing papers authored by Alexander Kowarik
This map shows the geographic impact of Alexander Kowarik'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 Alexander Kowarik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Kowarik more than expected).
Fields of papers citing papers by Alexander Kowarik
This network shows the impact of papers produced by Alexander Kowarik. 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 Alexander Kowarik. The network helps show where Alexander Kowarik may publish in the future.
Co-authorship network of co-authors of Alexander Kowarik
This figure shows the co-authorship network connecting the top 25 collaborators of Alexander Kowarik. A scholar is included among the top collaborators of Alexander Kowarik 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 Alexander Kowarik. Alexander Kowarik is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 5 | |
| 4 | Visualization and Imputation of Missing Values [R package VIM version 6.0.0] | 1 |
| 5 | 38 | |
| 6 | Imputation with the R Package VIMbreakdown → | 399 |
| 7 | 3 | |
| 8 | 3 | |
| 9 | 56 | |
| 10 | Development and Current Practice in Using R at Statistics Austria | 0 |
| 11 | 6 | |
| 12 | 3 | |
| 13 | 15 | |
| 14 | 2 | |
| 15 | 110 | |
| 16 | A computational and methodological framework for visualization and imputation of missing values: the R package VIM | 7 |
About Alexander Kowarik
Alexander Kowarik is a scholar working on Statistics and Probability, Management Science and Operations Research and Modeling and Simulation, having authored 16 papers that have together received 651 indexed citations. Recurring topics across this work include Data Analysis with R (4 papers), Statistical Methods and Bayesian Inference (3 papers) and demographic modeling and climate adaptation (3 papers). The work is most often cited by research in Statistics and Probability (97 citations), Artificial Intelligence (145 citations) and Experimental and Cognitive Psychology (45 citations). Alexander Kowarik has collaborated with scholars based in Austria, Switzerland and United States. Frequent co-authors include Matthias Templ, Peter Filzmoser, Olivier Dupriez, Siegfried Kasper, Andreas Alfons, Richard Frey, Dietmar Winkler, Edda Pjrek, A. Strnad and Ran Goldblatt. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Statistical Software and Computational Statistics & Data Analysis.
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.