Ludger Evers

414 total citations
17 papers, 256 citations indexed

About

Ludger Evers is a scholar working on Artificial Intelligence, Statistics and Probability and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ludger Evers has authored 17 papers receiving a total of 256 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 8 papers in Statistics and Probability and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ludger Evers's work include Statistical Methods and Inference (6 papers), Statistical Methods and Bayesian Inference (3 papers) and Bayesian Methods and Mixture Models (3 papers). Ludger Evers is often cited by papers focused on Statistical Methods and Inference (6 papers), Statistical Methods and Bayesian Inference (3 papers) and Bayesian Methods and Mixture Models (3 papers). Ludger Evers collaborates with scholars based in United Kingdom, Germany and Netherlands. Ludger Evers's co-authors include Claudia‐Martina Messow, Jochen Einbeck, Gerhard Tutz, Adrian Bowman, Wayne Jones, Michael Spence, Agostino Nobile, Matthijs Bonte, Tereza Neocleous and Timothy Heaton and has published in prestigious journals such as Bioinformatics, The Science of The Total Environment and Journal of Statistical Software.

In The Last Decade

Ludger Evers

14 papers receiving 236 citations

Peers

Ludger Evers

CVPR

Mohammed M. A. Almazah Saudi Arabia

Ernst Stadlober Austria

Arin Chaudhuri United States

Ziyuan Luo China

Hongwei Dong China

Gabriele Lombardi Italy

A. K. Gupta United States

Arkajyoti Saha India

Ryan Martin United States

Mohammed M. A. Almazah Saudi Arabia

Ludger Evers

25 ×0.4

36 ×0.8

53 ×1.2

11 ×0.3

CVPR

3 ×0.1

Citations per year, relative to Ludger Evers Ludger Evers (= 1×) peers Mohammed M. A. Almazah

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-authorship network of co-authors of Ludger Evers

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

All Works

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17 of 17 papers shown

Evers, Ludger, et al.. (2021). Functional distributional clustering using spatio-temporal data. Journal of Applied Statistics. 50(4). 909–926.

Evers, Ludger, et al.. (2018). Statistical modelling of groundwater contamination monitoring data: A comparison of spatial and spatiotemporal methods. The Science of The Total Environment. 652. 1339–1346. 30 indexed citations

Evers, Ludger & Timothy Heaton. (2017). Locally Adaptive Tree-Based Thresholding Using the treethresh Package in R. Journal of Statistical Software. 78(Code Snippet 2). 2 indexed citations

Silverman, Bernard W., et al.. (2017). Empirical Bayes Thresholding and Related Methods [R package EbayesThresh version 1.4-12].

Evers, Ludger, et al.. (2017). Efficient Bayesian inference for COM-Poisson regression models. Statistics and Computing. 28(3). 595–608. 23 indexed citations

Stuart‐Smith, Jane, et al.. (2015). A dynamic acoustic view of real-time change in word-final liquids in spontaneous Glaswegian. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 6 indexed citations

Evers, Ludger, et al.. (2015). Efficient and automatic methods for flexible regression on spatiotemporal data, with applications to groundwater monitoring. Environmetrics. 26(6). 431–441. 7 indexed citations

Evers, Ludger, et al.. (2014). Retrospective sampling in MCMC with an application to COM‐Poisson regression. Stat. 3(1). 273–290. 2 indexed citations

Jones, Wayne, et al.. (2014). A software tool for the spatiotemporal analysis and reporting of groundwater monitoring data. Environmental Modelling & Software. 55. 242–249. 27 indexed citations

10.

Einbeck, Jochen, et al.. (2010). DATA COMPRESSION AND REGRESSION THROUGH LOCAL PRINCIPAL CURVES AND SURFACES. International Journal of Neural Systems. 20(3). 177–192. 13 indexed citations

11.

Einbeck, Jochen & Ludger Evers. (2010). Localized regression on principal manifolds.. Durham Research Online (Durham University). 4 indexed citations

12.

Evers, Ludger & Timothy Heaton. (2009). Locally Adaptive Tree-Based Thresholding. Journal of Computational and Graphical Statistics. 18(4). 961–977. 10 indexed citations

13.

Evers, Ludger & Claudia‐Martina Messow. (2008). Sparse kernel methods for high-dimensional survival data. Bioinformatics. 24(14). 1632–1638. 61 indexed citations

14.

Evers, Ludger, et al.. (2007). Use of Iterative Proportional Fitting Algorithm for Combining Traffic Count Data with Missing Dimensions. Transportation Research Record Journal of the Transportation Research Board. 1993(1). 95–100. 1 indexed citations

15.

Evers, Ludger, et al.. (2007). The relationship between the ‘play the ball’ time, post-ruck action and the occurrence of perturbations in professional rugby league football. International Journal of Performance Analysis in Sport. 7(3). 18–25. 9 indexed citations

16.

Einbeck, Jochen, Gerhard Tutz, & Ludger Evers. (2005). Local principal curves. Statistics and Computing. 15(4). 301–313. 60 indexed citations

17.

Evers, Ludger, et al.. (2004). MSc in Bioinformatics: Statistical Data Mining. 1 indexed citations

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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