Jason L. Loeppky

1.6k citations
30 papers · 990 indexed · 1 hit paper · h-index 13

Jason L. Loeppky

29 papers receiving 946 citations

Hit Papers

Choosing the Sample Size of a Computer Experiment: A Prac...4962009202620142020100200300400

Peers

Jason L. Loeppky
Comparison fields: 5 of 139
  • Statistics, Probability and Uncertainty 265
  • Management Science and Operations Research 348
  • Computational Theory and Mathematics 395
  • Industrial and Manufacturing Engineering 69
  • Statistics and Probability 48
Replace James Gattiker with:
James Gattiker United States
John A. Cafeo United States
W.C.M. van Beers Netherlands
Olivier Roustant France
Susannah B. Schiller United States
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J. Sacks United States
David Ginsbourger Switzerland
Nathalie Bartoli France
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Citations per year

Countries citing papers authored by Jason L. Loeppky

Since Specialization
Citations

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

Fields of papers citing papers by Jason L. Loeppky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jason L. Loeppky. 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 Jason L. Loeppky. The network helps show where Jason L. Loeppky may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 201925
2 201914
3 20188
4 20182
5 201629
6 201630
7 20165
8 20156
9 20159
10 201524
11 20138
12 20123
13 20127
14 200976
15
Choosing the Sample Size of a Computer Experiment: A Practical Guidebreakdown →
2009496
16 200753
17 200730
18
Analyzing unreplicated blocked or split-plot fractional factorial designs
20031
19 200242
20 20024

About Jason L. Loeppky

Jason L. Loeppky is a scholar working on Management Science and Operations Research, Statistics, Probability and Uncertainty and Computational Theory and Mathematics, having authored 30 papers that have together received 990 indexed citations. Recurring topics across this work include Optimal Experimental Design Methods (11 papers), Advanced Multi-Objective Optimization Algorithms (9 papers), Gaussian Processes and Bayesian Inference (5 papers), Probabilistic and Robust Engineering Design (4 papers), Statistical Methods in Clinical Trials (3 papers), Statistical Methods and Bayesian Inference (2 papers), Water Systems and Optimization (2 papers) and Stellar, planetary, and galactic studies (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (265 citations), Management Science and Operations Research (348 citations) and Computational Theory and Mathematics (395 citations). Jason L. Loeppky has collaborated with scholars based in Canada, United States and India. Frequent co-authors include William J. Welch, Jerome Sacks, Leslie M. Moore, Brian J. Williams, R. R. Sitter, Solomon Tesfamariam, Jeff M. Szychowski, Greg F. Piepel, Golam Kabir and Rehan Sadiq. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Technometrics.

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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