William P. McCormick
- Statistics and Probability top 1%
- Statistical Methods and Inference 14
- Statistical Distribution Estimation and Applications 12
- Markov Chains and Monte Carlo Methods 4
- Finance top 2%
- Financial Risk and Volatility Modeling 28
- Stochastic processes and financial applications 18
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- Probability and Risk Models 30
- Mathematical Physics top 10%
- Stochastic processes and statistical mechanics 17
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- Bayesian Methods and Mixture Models 14
- Co-authors
- I. V. BasawaSomnath DattaRobert L. TaylorAtul MallikMichael R. ChernickTailen HsingRichard A. DavisJiayang Sun
- Journals
- Journal of the American Statistical Association (3 papers)The Annals of Statistics (3 papers)American Journal of Clinical Pathology (1 paper)
- Partner nations
- United StatesFranceTaiwan
In The Last Decade
William P. McCormick
66 papers receiving 759 citations
Peers
Comparison fields: 5 of 96
- Statistics and Probability 360
- Finance 435
- General Economics, Econometrics and Finance 184
- Management Science and Operations Research 188
- Mathematical Physics 98
Countries citing papers authored by William P. McCormick
This map shows the geographic impact of William P. McCormick'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 P. McCormick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William P. McCormick more than expected).
Fields of papers citing papers by William P. McCormick
This network shows the impact of papers produced by William P. McCormick. 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 P. McCormick. The network helps show where William P. McCormick may publish in the future.
Co-authorship network
The 25 scholars most cited alongside William P. McCormick, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 15 | |
| 2 | 2012 | 3 | |
| 3 | 2010 | 2 | |
| 4 | 2009 | 21 | |
| 5 | 2007 | 0 | |
| 6 | 2007 | 6 | |
| 7 | 2007 | 2 | |
| 8 | 2005 | 15 | |
| 9 | 2004 | 1 | |
| 10 | 2004 | 3 | |
| 11 | 2001 | 2 | |
| 12 | 2001 | 2 | |
| 13 | 2000 | 2 | |
| 14 | 1997 | 19 | |
| 15 | 1995 | 8 | |
| 16 | 1993 | 9 | |
| 17 | 1993 | 3 | |
| 18 | 1991 | 165 | |
| 19 | 1990 | 6 | |
| 20 | 1989 | 36 |
About William P. McCormick
William P. McCormick is a scholar working on Finance, Statistics and Probability and Management Science and Operations Research, having authored 70 papers that have together received 833 indexed citations. Recurring topics across this work include Probability and Risk Models (30 papers), Financial Risk and Volatility Modeling (28 papers), Stochastic processes and financial applications (18 papers), Stochastic processes and statistical mechanics (17 papers), Bayesian Methods and Mixture Models (14 papers), Statistical Methods and Inference (14 papers), Statistical Distribution Estimation and Applications (12 papers) and Markov Chains and Monte Carlo Methods (4 papers). The work is most often cited by research in Statistics and Probability (360 citations), Finance (435 citations) and General Economics, Econometrics and Finance (184 citations). William P. McCormick has collaborated with scholars based in United States, France and Taiwan. Frequent co-authors include I. V. Basawa, Somnath Datta, Robert L. Taylor, Atul Mallik, Michael R. Chernick, Tailen Hsing, Richard A. Davis, Jiayang Sun, Yongcheng Qi and Catherine Loader. Their work appears in journals such as Journal of the American Statistical Association, The Annals of Statistics and American Journal of Clinical Pathology.
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.