Alan M. Polansky

992 citations
41 papers · 686 indexed · h-index 14

Impact in

Papers in

Alan M. Polansky

39 papers receiving 661 citations

Peers

Alan M. Polansky
Comparison fields: 5 of 115
  • Statistics, Probability and Uncertainty 274
  • Statistics and Probability 287
  • Management Science and Operations Research 152
  • Medical Laboratory Technology 8
  • Industrial and Manufacturing Engineering 48
Replace Warren Gilchrist with:
Warren Gilchrist United Kingdom
Ismail Shah Pakistan
Dost Muhammad Khan Pakistan
G. Arthur Mihram United States
Gonzalo García‐Donato Spain
J. T. Webster United States
Adel Mohammadpour Iran
Matías Salibián‐Barrera Canada
Bikas K. Sinha India
Manuel Escabias Spain
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Citations per field
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Citations per year

Countries citing papers authored by Alan M. Polansky

Since Specialization
Citations

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

Fields of papers citing papers by Alan M. Polansky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alan M. Polansky. 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 Alan M. Polansky. The network helps show where Alan M. Polansky may publish in the future.

Co-authorship network

The 9 scholars most cited alongside Alan M. Polansky, 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 Alan M. Polansky Line = papers co-authored together Alan M. Polansky links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202310
2 20226
3 20211
4 201911
5 20146
6 20143
7 20093
8
Permutation methods for comparing process capabilities
20071
9 200613
10 20051
11 20033
12 20034
13 20022
14 200136
15 200070
16 199923
17 19999
18 199811
19 1998228
20 19977

About Alan M. Polansky

Alan M. Polansky is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty, Management Science and Operations Research, Control and Systems Engineering and Software, having authored 41 papers that have together received 686 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (18 papers), Statistical Methods and Inference (17 papers), Advanced Statistical Process Monitoring (15 papers), Statistical Methods and Bayesian Inference (7 papers), Statistical Distribution Estimation and Applications (5 papers), Control Systems and Identification (5 papers), Bayesian Methods and Mixture Models (4 papers) and Fault Detection and Control Systems (4 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (274 citations), Statistics and Probability (287 citations), Management Science and Operations Research (152 citations), Medical Laboratory Technology (8 citations) and Industrial and Manufacturing Engineering (48 citations). Alan M. Polansky has collaborated with scholars based in United States. Frequent co-authors include Robert Mason, Youn-Min Chou, William R. Schucany, Mark P. Fischer, Lei Hua, Rudy Guerra, S. N. U. A. Kirmani, Catherine E. Check and Michelle Xia. Their work appears in journals such as Journal of Quality Technology, Computational Statistics & Data Analysis, Quality and Reliability Engineering International, Quality Engineering and The American Statistician.

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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