Nadja Klein

1.7k citations
71 papers · 806 · h-index 15

Impact in

Papers in

Nadja Klein

65 papers receiving 788 citations

Peers

Nadja Klein
Comparison fields: 5 of 122
  • Statistics and Probability 301
  • Management Science and Operations Research 81
  • Ecological Modeling 26
  • Nature and Landscape Conservation 69
  • Economics and Econometrics 147
Replace Fernanda De Bastiani with:
Fernanda De Bastiani Brazil
Yves Tillé Switzerland
Hanfeng Chen United States
Y. Lee South Korea
Solomon W. Harrar United States
Carlo Gaetan Italy
Marcos O. Prates Brazil
Nikolaus Umlauf Austria
Tonio Di Battista Italy
L. I. Pettit United Kingdom
Nadja Klein relative to Fernanda De Bastiani Brazil Fernanda De Bastiani's profile →
Citations per field
00.5×3.3×
Fernanda De Bastiani · 1×
Citations per year

Countries citing papers authored by Nadja Klein

Since Specialization
Citations

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

Fields of papers citing papers by Nadja Klein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Nadja Klein, 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 Nadja Klein Line = papers co-authored together Nadja Klein links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201584
2 201781
3 201676
4 201458
5 201451
6 201443
7 201535
8 201535
9 201520
10 202120
11 202220
12 202120
13 202216
14 201716
15 201815
16 202214
17 201914
18 201814
19 202013
20 202411

About Nadja Klein

Nadja Klein is a scholar working on Statistics and Probability, Artificial Intelligence, Economics and Econometrics, Sociology and Political Science and Environmental Engineering, having authored 71 papers that have together received 806 indexed citations. Recurring topics across this work include Statistical Methods and Inference (30 papers), Statistical Methods and Bayesian Inference (19 papers), Bayesian Methods and Mixture Models (17 papers), Spatial and Panel Data Analysis (9 papers), Statistical Distribution Estimation and Applications (7 papers), Economic and Environmental Valuation (7 papers), Income, Poverty, and Inequality (6 papers) and Soil Geostatistics and Mapping (6 papers). The work is most often cited by research in Statistics and Probability (301 citations), Management Science and Operations Research (81 citations), Ecological Modeling (26 citations), Nature and Landscape Conservation (69 citations) and Economics and Econometrics (147 citations). Nadja Klein has collaborated with scholars based in Germany, Austria and Netherlands. Frequent co-authors include Thomas Kneib, Stefan Lang, Nikolaus Umlauf, Achim Zeileis, Stephan Klasen, Michel Denuit, Jonathon J. Valente, Adam S. Hadley, Urs G. Kormann and Teja Tscharntke. Their work appears in journals such as Journal of Computational and Graphical Statistics, Statistics and Computing, PLoS ONE, The Annals of Applied Statistics and BMC Medical Research Methodology.

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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