Jim Albert

1.9k citations
53 papers · 717 · h-index 14

Impact in

Papers in

Jim Albert

49 papers receiving 649 citations

Peers

Jim Albert
Comparison fields: 5 of 134
  • Statistics and Probability 273
  • General Decision Sciences 21
  • Economics and Econometrics 262
  • Statistics, Probability and Uncertainty 47
  • Management Science and Operations Research 75
Replace Gunther Schauberger with:
Gunther Schauberger Germany
David H. Annis United States
Katherine K. Wallman United States
Mark Finster United States
Vicente Núñez‐Antón Spain
Stephen E. Fienberg United States
Cleo Youtz United States
Robert G. Lehnen United States
Tue Tjur Denmark
David R. Bellhouse Canada
Jim Albert relative to Gunther Schauberger Germany Gunther Schauberger's profile →
Citations per field
00.5×9.4×
Gunther Schauberger · 1×
Citations per year

Countries citing papers authored by Jim Albert

Since Specialization
Citations

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

Fields of papers citing papers by Jim Albert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Jim Albert, 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 Jim Albert Line = papers co-authored together Jim Albert links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009159
2 199585
3 200757
4 199741
5 201926
6 199326
7 200825
8 199323
9 199722
10 200522
11 200121
12 200217
13 201315
14 199513
15 201112
16 201812
17 199710
18 199310
19 20049
20 19948

About Jim Albert

Jim Albert is a scholar working on Economics and Econometrics, Statistics and Probability, Artificial Intelligence, Biomedical Engineering and Nature and Landscape Conservation, having authored 53 papers that have together received 717 indexed citations. Recurring topics across this work include Sports Analytics and Performance (26 papers), Statistics Education and Methodologies (11 papers), Data Analysis with R (10 papers), Statistical Methods and Bayesian Inference (9 papers), Sports Dynamics and Biomechanics (7 papers), Statistical Methods and Inference (5 papers), Forest ecology and management (3 papers) and Advanced Statistical Methods and Models (3 papers). The work is most often cited by research in Statistics and Probability (273 citations), General Decision Sciences (21 citations), Economics and Econometrics (262 citations), Statistics, Probability and Uncertainty (47 citations) and Management Science and Operations Research (75 citations). Jim Albert has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Siddhartha Chib, Ruud H. Koning, Jingchen Hu, Maria L. Rizzo, James J. Cochran, Benjamin S. Baumer, Stephanie Kovalchik, Hal S. Stern, Nadia Martin and John J. Weber. Their work appears in journals such as Journal of the American Statistical Association, Journal of Quantitative Analysis in Sports, The American Statistician, Biometrika and Wiley Interdisciplinary Reviews Computational Statistics.

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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