D. Nolan

700 citations
13 papers · 448 · h-index 9

Impact in

Papers in

    • Statistical Methods and Inference 6
    • Advanced Statistical Methods and Models 5
    • Statistics Education and Methodologies 3
    • Statistical Distribution Estimation and Applications 1
    • Bayesian Methods and Mixture Models 2

D. Nolan

11 papers receiving 404 citations

Peers

D. Nolan
Comparison fields: 5 of 103
  • Statistics and Probability 273
  • Statistics, Probability and Uncertainty 60
  • Computer Science Applications 29
  • Information Systems and Management 30
  • Management Information Systems 36
Replace Marietta J. Tretter with:
Marietta J. Tretter United States
Ali Ahmed Egypt
Deirdre O'Brien United States
Shane P. Pederson United States
V. A. Sposito United States
Yuexiao Dong United States
Weiwei Guo China
H. E. Reinhardt United States
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Heather Battey United Kingdom
D. Nolan relative to Marietta J. Tretter United States Marietta J. Tretter's profile →
Citations per field
00.5×
Marietta J. Tretter · 1×
Citations per year

Countries citing papers authored by D. Nolan

Since Specialization
Citations

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

Fields of papers citing papers by D. Nolan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside D. Nolan, 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 D. Nolan Line = papers co-authored together D. Nolan links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 2015146
2 198898
3 199945
4 199245
5 199134
6 199531
7 199916
8 199412
9 199912
10 19926
11 19953
12 20230
13 20050

About D. Nolan

D. Nolan is a scholar working on Statistics and Probability, Artificial Intelligence, Control and Systems Engineering, Social Psychology and Radiological and Ultrasound Technology, having authored 13 papers that have together received 448 indexed citations. Recurring topics across this work include Statistical Methods and Inference (6 papers), Advanced Statistical Methods and Models (5 papers), Statistics Education and Methodologies (3 papers), Bayesian Methods and Mixture Models (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Youth Development and Social Support (1 paper), Statistical Distribution Estimation and Applications (1 paper) and Soil Geostatistics and Mapping (1 paper). The work is most often cited by research in Statistics and Probability (273 citations), Statistics, Probability and Uncertainty (60 citations), Computer Science Applications (29 citations), Information Systems and Management (30 citations) and Management Information Systems (36 citations). D. Nolan has collaborated with scholars based in United States, New Zealand and Ireland. Frequent co-authors include J. S. Marron, Terence P. Speed, Olaf Hall-Holt, Johanna Hardin, Benjamin S. Baumer, Nicholas J. Horton, Roger D. Peng, Roger W. Hoerl, Duncan Temple Lang and Mark Daniel Ward. Their work appears in journals such as The American Statistician, Journal of Multivariate Analysis, Biometrika, Stochastic Processes and their Applications and Radiation Protection Dosimetry.

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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