Ludger Evers

414 citations
17 papers · 256 · h-index 8

Impact in

Papers in

    • Bayesian Methods and Mixture Models 3
    • Neural Networks and Applications 2
    • Statistical Methods and Inference 6
    • Statistical Methods and Bayesian Inference 3
    • Advanced Statistical Methods and Models 2

Ludger Evers

14 papers receiving 236 citations

Peers

Ludger Evers
Comparison fields: 5 of 96
  • Statistics and Probability 48
  • Computational Mathematics 3
  • Geochemistry and Petrology 19
  • Environmental Engineering 45
  • Artificial Intelligence 67
Replace Mohammed M. A. Almazah with:
Mohammed M. A. Almazah Saudi Arabia
José Rodríguez Avi Spain
Ernst Stadlober Austria
Yves Deville France
José Mira Spain
Ryan Martin United States
Cheng Qian China
Jakob W. Messner Austria
Arin Chaudhuri United States
Ludger Evers relative to Mohammed M. A. Almazah Saudi Arabia Mohammed M. A. Almazah's profile →
Citations per field
00.5×10×15×21×
Mohammed M. A. Almazah · 1×
Citations per year

Countries citing papers authored by Ludger Evers

Since Specialization
Citations

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

Fields of papers citing papers by Ludger Evers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside Ludger Evers, 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 Ludger Evers Line = papers co-authored together Ludger Evers links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 200861
2 200560
3 201830
4 201427
5 201723
6 201013
7 200910
8 20079
9 20157
10
A dynamic acoustic view of real-time change in word-final liquids in spontaneous Glaswegian
20156
11
Localized regression on principal manifolds.
20104
12 20142
13 20172
14
MSc in Bioinformatics: Statistical Data Mining
20041
15 20071
16 20210
17
Empirical Bayes Thresholding and Related Methods [R package EbayesThresh version 1.4-12]
20170

About Ludger Evers

Ludger Evers is a scholar working on Artificial Intelligence, Statistics and Probability, Computer Vision and Pattern Recognition, Environmental Engineering and Molecular Biology, having authored 17 papers that have together received 256 indexed citations. Recurring topics across this work include Statistical Methods and Inference (6 papers), Statistical Methods and Bayesian Inference (3 papers), Soil Geostatistics and Mapping (3 papers), Bayesian Methods and Mixture Models (3 papers), Neural Networks and Applications (2 papers), Advanced Statistical Methods and Models (2 papers), Statistical and numerical algorithms (2 papers) and Image and Signal Denoising Methods (2 papers). The work is most often cited by research in Statistics and Probability (48 citations), Computational Mathematics (3 citations), Geochemistry and Petrology (19 citations), Environmental Engineering (45 citations) and Artificial Intelligence (67 citations). Ludger Evers has collaborated with scholars based in United Kingdom, Germany and Netherlands. Frequent co-authors include Claudia‐Martina Messow, Jochen Einbeck, Gerhard Tutz, Wayne Jones, Adrian Bowman, Michael Spence, Timothy Heaton, Matthijs Bonte, Tereza Neocleous and Agostino Nobile. Their work appears in journals such as Statistics and Computing, Bioinformatics, Journal of Statistical Software, Journal of Computational and Graphical Statistics and Environmental Modelling & Software.

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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