Nancy Heckman

2.3k citations
40 papers · 1.7k · h-index 15

Impact in

Papers in

    • Statistical Methods and Inference 20
    • Advanced Statistical Methods and Models 9
    • Statistical Methods in Clinical Trials 4
    • Statistical Methods and Bayesian Inference 3
    • Bayesian Methods and Mixture Models 6

Nancy Heckman

37 papers receiving 1.5k citations

Peers

Nancy Heckman
Comparison fields: 5 of 127
  • Statistics and Probability 690
  • Ecology, Evolution, Behavior and Systematics 359
  • Genetics 398
  • Statistics, Probability and Uncertainty 82
  • Developmental Biology 24
Replace R. N. Curnow with:
R. N. Curnow United Kingdom
Robert V. Foutz United States
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Pierre Duchesne Canada
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Citations per field
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Citations per year

Countries citing papers authored by Nancy Heckman

Since Specialization
Citations

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

Fields of papers citing papers by Nancy Heckman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Nancy Heckman, 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 Nancy Heckman Line = papers co-authored together Nancy Heckman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1986306
2 1989305
3 1995264
4 1993228
5 199574
6 200073
7 200069
8 200041
9 201638
10 201838
11 200829
12 199725
13 200422
14 198815
15 200115
16 201512
17 201311
18 200110
19 20139
20 20019

About Nancy Heckman

Nancy Heckman is a scholar working on Statistics and Probability, Artificial Intelligence, Control and Systems Engineering, Management Science and Operations Research and Genetics, having authored 40 papers that have together received 1.7k indexed citations. Recurring topics across this work include Statistical Methods and Inference (20 papers), Advanced Statistical Methods and Models (9 papers), Control Systems and Identification (6 papers), Bayesian Methods and Mixture Models (6 papers), Statistical Methods in Clinical Trials (4 papers), Animal Behavior and Reproduction (3 papers), Optimal Experimental Design Methods (3 papers) and Statistical Methods and Bayesian Inference (3 papers). The work is most often cited by research in Statistics and Probability (690 citations), Ecology, Evolution, Behavior and Systematics (359 citations), Genetics (398 citations), Statistics, Probability and Uncertainty (82 citations) and Developmental Biology (24 citations). Nancy Heckman has collaborated with scholars based in Canada, United States and Australia. Frequent co-authors include Mark Kirkpatrick, Jianqing Fan, M. P. Wand, Dolph Schluter, Trevor D. Price, J. O. Ramsay, Peter Hall, Richard Gomulkiewicz, Patrick A. Carter and Irène Gijbels. Their work appears in journals such as Journal of the American Statistical Association, The Annals of Statistics, Journal of Computational and Graphical Statistics, The American Naturalist and Proceedings of the Royal Society B Biological Sciences.

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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