M. Pitt
- Statistics and Probability top 0.5%
- Statistical Methods and Inference 8
- Statistical Methods and Bayesian Inference 4
- Finance top 1%
- Financial Risk and Volatility Modeling 13
- Artificial Intelligence top 0.5%
- Bayesian Methods and Mixture Models 8
- Signal Processing top 5%
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- Particle Detector Development and Performance 10
- High-Energy Particle Collisions Research 4
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- Radiation Detection and Scintillator Technologies 7
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- Forecasting Techniques and Applications 5
- Co-authors
- Neil ShephardRobert KohnDavid ChanRandal DoucPaolo GiordaniGeorge DeligiannidisSheheryar MalikAdrian Banning
- Journals
- Journal of Instrumentation (6 papers)Journal of the American Statistical Association (3 papers)Journal of Econometrics (2 papers)
- Partner nations
- United KingdomIsraelAustralia
In The Last Decade
M. Pitt
41 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Statistics and Probability 505
- Finance 564
- Artificial Intelligence 1.6k
- General Economics, Econometrics and Finance 208
- Signal Processing 182
Countries citing papers authored by M. Pitt
This map shows the geographic impact of M. Pitt'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 M. Pitt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Pitt more than expected).
Fields of papers citing papers by M. Pitt
This network shows the impact of papers produced by M. Pitt. 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 M. Pitt. The network helps show where M. Pitt may publish in the future.
Co-authorship network
The 25 scholars most cited alongside M. Pitt, 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 | 2024 | 1 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 0 | |
| 4 | 2023 | 1 | |
| 5 | 2022 | 3 | |
| 6 | 2020 | 12 | |
| 7 | 2018 | 16 | |
| 8 | 2014 | 1 | |
| 9 | 2014 | 8 | |
| 10 | 2013 | 13 | |
| 11 | On Some Properties of Markov Chain Monte Carlo Simulation Methods Based on the Particle Filter | 2012 | 4 |
| 12 | 2006 | 74 | |
| 13 | for the REACT Trial Investigators. Rescue Angioplasty after Failed Thrombolytic Therapy for Acute Myocardial Infarction | 2005 | 35 |
| 14 | 2005 | 276 | |
| 15 | 2002 | 39 | |
| 16 | 1998 | 1 | |
| 17 | 1996 | 1 | |
| 18 | 1996 | 13 | |
| 19 | 1994 | 3 | |
| 20 | 1993 | 13 |
About M. Pitt
M. Pitt is a scholar working on Statistics and Probability, Finance, Nuclear and High Energy Physics, Radiation and Management Science and Operations Research, having authored 43 papers that have together received 3.4k indexed citations. Recurring topics across this work include Financial Risk and Volatility Modeling (13 papers), Particle Detector Development and Performance (10 papers), Bayesian Methods and Mixture Models (8 papers), Statistical Methods and Inference (8 papers), Radiation Detection and Scintillator Technologies (7 papers), Forecasting Techniques and Applications (5 papers), Statistical Methods and Bayesian Inference (4 papers) and High-Energy Particle Collisions Research (4 papers). The work is most often cited by research in Statistics and Probability (505 citations), Finance (564 citations), Artificial Intelligence (1.6k citations), General Economics, Econometrics and Finance (208 citations) and Signal Processing (182 citations). M. Pitt has collaborated with scholars based in United Kingdom, Israel and Australia. Frequent co-authors include Neil Shephard, Robert Kohn, David Chan, Randal Douc, Paolo Giordani, George Deligiannidis, Sheheryar Malik, Adrian Banning, Keith R. Abrams and Peter M. Schofield. Their work appears in journals such as Journal of Instrumentation, Journal of the American Statistical Association, Journal of Econometrics, Neuropediatrics and Biometrika.
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.