Michael D. McKay

18.7k total citations · 4 hit papers
26 papers, 13.8k citations indexed

About

Michael D. McKay is a scholar working on Statistics, Probability and Uncertainty, Management Science and Operations Research and Computational Theory and Mathematics. According to data from OpenAlex, Michael D. McKay has authored 26 papers receiving a total of 13.8k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Statistics, Probability and Uncertainty, 9 papers in Management Science and Operations Research and 6 papers in Computational Theory and Mathematics. Recurrent topics in Michael D. McKay's work include Probabilistic and Robust Engineering Design (10 papers), Advanced Multi-Objective Optimization Algorithms (5 papers) and Optimal Experimental Design Methods (5 papers). Michael D. McKay is often cited by papers focused on Probabilistic and Robust Engineering Design (10 papers), Advanced Multi-Objective Optimization Algorithms (5 papers) and Optimal Experimental Design Methods (5 papers). Michael D. McKay collaborates with scholars based in United States and Netherlands. Michael D. McKay's co-authors include Richard J. Beckman, W. J. Conover, Keith Baggerly, Brian J. Williams, Katherine Campbell, Leslie M. Moore, J. Morrison, J.C. Helton, Michael S. Hamada and James Coons and has published in prestigious journals such as Journal of the American Statistical Association, Technometrics and Computer Physics Communications.

In The Last Decade

Michael D. McKay

26 papers receiving 13.2k citations

Hit Papers

A Comparison of Three Methods for Selecting Val... 1979 2026 1994 2010 2000 1979 1979 2000 1000 2.0k 3.0k 4.0k 5.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code
    2000 5.5k citations Michael D. McKay, Richard J. Beckman et al. Technometrics profile →
  2. A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code
    1979 3.0k citations Michael D. McKay et al. Technometrics profile →
  3. Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code
    1979 2.4k citations Michael D. McKay, Richard J. Beckman et al. Technometrics profile →
  4. A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code
    2000 1.8k citations Michael D. McKay, Richard J. Beckman et al. Technometrics profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael D. McKay United States 20 3.4k 2.9k 2.3k 2.0k 1.7k 26 13.8k
Richard J. Beckman United States 22 2.7k 0.8× 2.2k 0.8× 2.0k 0.9× 1.8k 0.9× 1.4k 0.8× 73 16.2k
I. M. Sobol Russia 24 5.3k 1.6× 1.7k 0.6× 2.4k 1.1× 910 0.5× 1.7k 1.0× 73 12.3k
Max D. Morris United States 23 2.5k 0.7× 2.0k 0.7× 1.1k 0.5× 1.5k 0.7× 1.5k 0.9× 111 8.4k
Stefano Tarantola Italy 50 6.0k 1.8× 1.5k 0.5× 3.2k 1.4× 1.6k 0.8× 4.1k 2.4× 103 20.6k
Francesca Campolongo Italy 22 3.9k 1.1× 1.0k 0.3× 2.1k 0.9× 847 0.4× 2.6k 1.5× 36 12.9k
Toby J. Mitchell United States 29 3.4k 1.0× 4.6k 1.6× 909 0.4× 3.4k 1.7× 742 0.4× 74 12.1k
J.C. Helton United States 37 5.6k 1.6× 1.4k 0.5× 1.7k 0.8× 1.2k 0.6× 1.4k 0.8× 169 9.7k
Andrea Saltelli Italy 59 8.6k 2.5× 2.1k 0.7× 4.4k 1.9× 2.3k 1.2× 5.2k 3.1× 181 28.4k
Jerome Sacks United States 29 3.6k 1.1× 4.6k 1.6× 771 0.3× 3.6k 1.8× 632 0.4× 66 9.6k
Anthony O’Hagan United Kingdom 47 3.6k 1.0× 1.8k 0.6× 854 0.4× 2.0k 1.0× 1.1k 0.7× 129 13.5k

Countries citing papers authored by Michael D. McKay

Since Specialization
Citations

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

Fields of papers citing papers by Michael D. McKay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael D. McKay

This figure shows the co-authorship network connecting the top 25 collaborators of Michael D. McKay. A scholar is included among the top collaborators of Michael D. McKay based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael D. McKay. Michael D. McKay is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Haines, B. M., Michael D. McKay, HyeongKae Park, et al.. (2022). The development of a high-resolution Eulerian radiation-hydrodynamics simulation capability for laser-driven Hohlraums. Physics of Plasmas. 29(8). 22 indexed citations
2.
Moore, Leslie M., et al.. (2006). Combined array experiment design. Reliability Engineering & System Safety. 91(10-11). 1281–1289. 11 indexed citations
3.
Helton, J.C., Roger Cooke, Michael D. McKay, & Andrea Saltelli. (2006). Sensitivity Analysis of Model Output: SAMO 2004. Reliability Engineering & System Safety. 91(10-11). 1105–1108. 25 indexed citations
4.
Campbell, Katherine, Michael D. McKay, & Brian J. Williams. (2006). Sensitivity analysis when model outputs are functions. Reliability Engineering & System Safety. 91(10-11). 1468–1472. 115 indexed citations
5.
Gattiker, James, Dave Higdon, Sallie Keller‐McNulty, et al.. (2006). Combining experimental data and computer simulations, with an application to flyer plate experiments. Bayesian Analysis. 1(4). 63 indexed citations
6.
Morris, Max D., Leslie M. Moore, & Michael D. McKay. (2005). Sampling plans based on balanced incomplete block designs for evaluating the importance of computer model inputs. Quality Engineering. 136(9). 3203–3220. 1 indexed citations
7.
McKay, Michael D., Richard J. Beckman, & W. J. Conover. (2000). A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code. Technometrics. 42(1). 55–55. 5480 indexed citations breakdown →
8.
McKay, Michael D., Richard J. Beckman, & W. J. Conover. (2000). A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code. Technometrics. 42(1). 55–61. 1828 indexed citations breakdown →
9.
McKay, Michael D., et al.. (2000). Critique of and Limitations on the Use of Expert Judgements in Accident Consequence Uncertainty Analysis. Radiation Protection Dosimetry. 90(3). 325–330. 24 indexed citations
10.
McKay, Michael D., et al.. (1999). Evaluating prediction uncertainty in simulation models. Computer Physics Communications. 117(1-2). 44–51. 69 indexed citations
11.
Beckman, Richard J., Keith Baggerly, & Michael D. McKay. (1996). Creating synthetic baseline populations. Transportation Research Part A Policy and Practice. 30(6). 415–429. 335 indexed citations
12.
Helton, J.C., et al.. (1995). Robustness of an uncertainty and sensitivity analysis of early exposure results with the MACCS reactor accident consequence model. Reliability Engineering & System Safety. 48(2). 129–148. 40 indexed citations
13.
McKay, Michael D.. (1992). The Special Education Handbook. Archives of Disease in Childhood. 67(3). 353–354. 2 indexed citations
14.
McKay, Michael D.. (1992). Latin hypercube sampling as a tool in uncertainty analysis of computer models. 557–564. 170 indexed citations
15.
Beckman, Richard J. & Michael D. McKay. (1987). Monte Carlo Estimation Under Different Distributions Using the Same Simulation. Technometrics. 29(2). 153–160. 32 indexed citations
16.
McKay, Michael D. & Michael S. Waterman. (1982). Self-descriptive strings. The Mathematical Gazette. 66(435). 1–4. 3 indexed citations
17.
McKay, Michael D. & Richard J. Beckman. (1980). Comments. Communication in Statistics- Theory and Methods. 9(17). 1859–1861. 2 indexed citations
18.
McKay, Michael D., Richard J. Beckman, & W. J. Conover. (1979). Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code. Technometrics. 21(2). 239–245. 2431 indexed citations breakdown →
19.
McKay, Michael D., et al.. (1979). A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code. Technometrics. 21(2). 239–239. 2960 indexed citations breakdown →
20.
McKay, Michael D., David S. Moore, & James Yackel. (1975). Applicable Finite Mathematics.. Journal of the American Statistical Association. 70(351). 733–733. 2 indexed citations

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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