Thomas Kneib

11.7k total citations · 2 hit papers
211 papers, 7.3k citations indexed

About

Thomas Kneib is a scholar working on Statistics and Probability, Economics and Econometrics and Artificial Intelligence. According to data from OpenAlex, Thomas Kneib has authored 211 papers receiving a total of 7.3k indexed citations (citations by other indexed papers that have themselves been cited), including 103 papers in Statistics and Probability, 54 papers in Economics and Econometrics and 40 papers in Artificial Intelligence. Recurrent topics in Thomas Kneib's work include Statistical Methods and Inference (82 papers), Statistical Methods and Bayesian Inference (71 papers) and Spatial and Panel Data Analysis (27 papers). Thomas Kneib is often cited by papers focused on Statistical Methods and Inference (82 papers), Statistical Methods and Bayesian Inference (71 papers) and Spatial and Panel Data Analysis (27 papers). Thomas Kneib collaborates with scholars based in Germany, Austria and United States. Thomas Kneib's co-authors include Achim Zeileis, Anne‐Laure Boulesteix, Carolin Strobl, Thomas Augustin, Ludwig Fahrmeir, Stefan Lang, Torsten Hothorn, Nadja Klein, Sonja Greven and Fabian Sobotka and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and PLoS ONE.

In The Last Decade

Thomas Kneib

200 papers receiving 7.0k citations

Hit Papers

Conditional variable importance for random forests 2008 2026 2014 2020 2008 2013 500 1000 1.5k 2.0k

Peers

Thomas Kneib
Comparison fields: 5 of 220
  • Statistics and Probability 1.8k
  • Artificial Intelligence 1.1k
  • Economics and Econometrics 928
  • Ecology 875
  • Global and Planetary Change 744
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Citations per field, relative to Thomas Kneib
Thomas Kneib · 1×
Citations per year, relative to Thomas Kneib
Thomas Kneib · 1×

Countries citing papers authored by Thomas Kneib

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Kneib

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Kneib

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Kneib. A scholar is included among the top collaborators of Thomas Kneib 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 Thomas Kneib. Thomas Kneib is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 15
3 12
4 0
5 0
6 0
7 4
8 1
9 0
10 15
11 7
12 1
13 17
14
Generalized additive models for location, scale and shape for program evaluation: A guide to practice
2
15 6
16
A New Semiparametric Approach to Analysing Conditional Income Distributions
1
17
Model-Based Boosting
21
18
Discussion on "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations" by Rue, H., Martino, S. and Chopin, N
1
19
BayesX: Analyzing Bayesian Structural Additive Regression Models
2
20 8

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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