William I. Notz

5.0k total citations · 1 hit paper
48 papers, 3.4k citations indexed

About

William I. Notz is a scholar working on Management Science and Operations Research, Computational Theory and Mathematics and Statistics and Probability. According to data from OpenAlex, William I. Notz has authored 48 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Management Science and Operations Research, 20 papers in Computational Theory and Mathematics and 15 papers in Statistics and Probability. Recurrent topics in William I. Notz's work include Optimal Experimental Design Methods (30 papers), Advanced Multi-Objective Optimization Algorithms (20 papers) and Statistical Methods in Clinical Trials (7 papers). William I. Notz is often cited by papers focused on Optimal Experimental Design Methods (30 papers), Advanced Multi-Objective Optimization Algorithms (20 papers) and Statistical Methods in Clinical Trials (7 papers). William I. Notz collaborates with scholars based in United States, Australia and India. William I. Notz's co-authors include Thomas J. Santner, Brian J. Williams, Theodore T. Allen, D. Huang, Brian Williams, RA Miller, Donald L. Bartel, Dibyen Majumdar, Michael A. Fligner and Jonathan Bart and has published in prestigious journals such as Journal of the American Statistical Association, Technometrics and Mathematics of Computation.

In The Last Decade

William I. Notz

45 papers receiving 3.2k citations

Hit Papers

The Design and Analysis of Computer Experiments 2003 2026 2010 2018 2003 500 1000 1.5k
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. The Design and Analysis of Computer Experiments
    2003 1.5k citations Thomas J. Santner, Brian J. Williams et al. Springer series in statistics profile →

Peers

William I. Notz
V. Roshan Joseph United States
Agus Sudjianto United States
Donald Ylvisaker United States
Daniel W. Apley United States
Robert B. Gramacy United States
Agnes M. Herzberg United Kingdom
William L. Oberkampf United States
Laura Swiler United States
András Sóbester United Kingdom
Klaus Schittkowski Germany
V. Roshan Joseph United States
William I. Notz
Citations per year, relative to William I. Notz William I. Notz (= 1×) peers V. Roshan Joseph

Countries citing papers authored by William I. Notz

Since Specialization
Citations

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

Fields of papers citing papers by William I. Notz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William I. Notz. 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 William I. Notz. The network helps show where William I. Notz may publish in the future.

Co-authorship network of co-authors of William I. Notz

This figure shows the co-authorship network connecting the top 25 collaborators of William I. Notz. A scholar is included among the top collaborators of William I. Notz 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 William I. Notz. William I. Notz 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.
Han, Gang, Thomas J. Santner, William I. Notz, & Donald L. Bartel. (2009). Prediction for Computer Experiments Having Quantitative and Qualitative Input Variables. Technometrics. 51(3). 278–288. 59 indexed citations
2.
Notz, William I. & Arun Kumar. (2008). Sequential calibration of computer models. 3 indexed citations
3.
Notz, William I., et al.. (2006). Statistical Tests of Real‐Money versus Play‐Money Prediction Markets. Electronic Markets. 16(1). 63–69. 49 indexed citations
4.
Huang, D., et al.. (2006). Global Optimization of Stochastic Black-Box Systems via Sequential Kriging Meta-Models. Journal of Global Optimization. 34(3). 441–466. 443 indexed citations
5.
Graham, Petra L., William I. Notz, Dennis K. Pearl, & Elizabeth A. Stasny. (2003). Electronic resources: the Ohio state university EESEE project. Journal of Applied Mathematics and Decision Sciences. 7(2). 85–92.
6.
Santner, Thomas J., Brian J. Williams, & William I. Notz. (2003). The Design and Analysis of Computer Experiments. Springer series in statistics. 1547 indexed citations breakdown →
7.
Notz, William I., et al.. (2002). Sequential design of computer experiments for robust parameter design. 11 indexed citations
8.
Bryce, G. Rex, Robert Gould, William I. Notz, & Roxy Peck. (2001). Curriculum Guidelines for Bachelor of Science Degrees in Statistical Science. The American Statistician. 55(1). 7–13. 28 indexed citations
9.
Notz, William I., Thomas J. Santner, & Brian J. Williams. (2000). Sequential design of computer experiments to minimize integrated response functions. 80 indexed citations
10.
Notz, William I., Thomas J. Lorenzen, & Virgil L. Anderson. (1994). Design of Experiments: A No-Name Approach.. Journal of the American Statistical Association. 89(427). 1139–1139. 1 indexed citations
11.
Notz, William I., et al.. (1994). Robustness to the unavailability of data in block designs. Metrika. 41(1). 263–275. 3 indexed citations
12.
Notz, William I.. (1992). The Engineering Statistician's Guide to Continuous Bivariate Distributions. Technometrics. 34(4). 489–489. 4 indexed citations
13.
Notz, William I., et al.. (1992). The Engineering Statistician's Guide to Continuous Bivariate Distributions. Technometrics. 34(4). 489–489. 12 indexed citations
14.
Toman, Blaza & William I. Notz. (1991). Bayesian optimal experimental design for treatment—control comparisons in the presence of two-way heterogeneity. Journal of Statistical Planning and Inference. 27(1). 51–63. 5 indexed citations
15.
Notz, William I., Sudhir Gupta, & Rahul Mukerjee. (1990). A Calculus for Factorial Arrangements.. Journal of the American Statistical Association. 85(412). 1179–1179. 15 indexed citations
16.
Notz, William I.. (1989). Optimal designs for regression models with possible bias. Journal of Statistical Planning and Inference. 22(1). 43–54. 14 indexed citations
17.
Notz, William I., et al.. (1989). Optimal Design and Analysis of Experiments.. Journal of the American Statistical Association. 84(408). 1102–1102. 27 indexed citations
18.
Bradley, Ralph A., et al.. (1985). Nearly Trend-Free Block Designs. Journal of the American Statistical Association. 80(392). 985–985. 4 indexed citations
19.
Bradley, Ralph A., et al.. (1985). Nearly Trend-Free Block Designs. Journal of the American Statistical Association. 80(392). 985–992. 17 indexed citations
20.
Notz, William I.. (1982). Minimal point second order designs. Journal of Statistical Planning and Inference. 6(1). 47–58. 25 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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