Daniel R. Jeske

2.8k citations
125 papers · 2.0k indexed · h-index 25
Topics
Advanced Statistical Process Monitoring (15 papers)Statistical Methods and Bayesian Inference (15 papers)Advanced Statistical Methods and Models (14 papers)

In The Last Decade

Daniel R. Jeske

119 papers receiving 1.9k citations

Peers

Daniel R. Jeske
Comparison fields: 5 of 180
  • Statistics and Probability 326
  • Software 249
  • Computer Networks and Communications 242
  • Safety, Risk, Reliability and Quality 231
  • Molecular Biology 206
Replace M. J. Crowder with:
M. J. Crowder United Kingdom
Ping Ma China
Alexander Statnikov United States
James R. Jackson United States
Ray A. Waller United States
Marco Ramoni United States
Alice Richardson Australia
Ping Zhang China
Lara Lusa Slovenia
A.H. Marshall United Kingdom
Daniel R. Jeske relative to M. J. Crowder United Kingdom M. J. Crowder's profile →
Citations per field
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Citations per year

Countries citing papers authored by Daniel R. Jeske

Since Specialization
Citations

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

Fields of papers citing papers by Daniel R. Jeske

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel R. Jeske. 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 Daniel R. Jeske. The network helps show where Daniel R. Jeske may publish in the future.

Co-authorship network of co-authors of Daniel R. Jeske

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel R. Jeske. A scholar is included among the top collaborators of Daniel R. Jeske 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 Daniel R. Jeske. Daniel R. Jeske 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
#WorkIndexed citations
1 0
2 3
3 38
4 5
5 33
6
Approximate Prediction Intervals for Generalized Linear Mixed Models Having a Single Random Factor
1
7 2
8 1
9 4
10 68
11 19
12 7
13 2
14
Mining and Tracking Massive Text Data
2
15 0
16 109
17 3
18 21
19 15
20 124

About Daniel R. Jeske

Daniel R. Jeske is a scholar working on Statistics and Probability, Software and Statistics, Probability and Uncertainty, having authored 125 papers that have together received 2.0k indexed citations. Recurring topics across this work include Advanced Statistical Process Monitoring (15 papers), Statistical Methods and Bayesian Inference (15 papers) and Advanced Statistical Methods and Models (14 papers). The work is most often cited by research in Software (249 citations), Statistics and Probability (326 citations) and Statistics, Probability and Uncertainty (191 citations). Daniel R. Jeske has collaborated with scholars based in United States, Germany and Russia. Frequent co-authors include David A. Harville, Jeffrey A. Klein, Hoang Pham, Xuemei Zhang, Ashwin Sampath, Jessica L. Malisch, Enrico L. Rezende, Theodore Garland, Wendy Saltzman and Fernando Ribeiro Gomes. Their work appears in journals such as Journal of Clinical Oncology, Journal of the American Statistical Association and Gastroenterology.

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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