James C. Fu

2.8k total citations
81 papers, 2.0k citations indexed

About

James C. Fu is a scholar working on Statistics and Probability, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, James C. Fu has authored 81 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Statistics and Probability, 31 papers in Artificial Intelligence and 16 papers in Management Science and Operations Research. Recurrent topics in James C. Fu's work include Bayesian Methods and Mixture Models (27 papers), Statistical Distribution Estimation and Applications (17 papers) and Reliability and Maintenance Optimization (13 papers). James C. Fu is often cited by papers focused on Bayesian Methods and Mixture Models (27 papers), Statistical Distribution Estimation and Applications (17 papers) and Reliability and Maintenance Optimization (13 papers). James C. Fu collaborates with scholars based in Canada, Taiwan and United States. James C. Fu's co-authors include Markos V. Koutras, Wendy Lou, Min‐Te Chao, Liqun Wang, Hansheng Xie, Fred Spiring, Galit Shmueli, Zhidong Bai, Zhensheng Zhang and Smiley W. Cheng and has published in prestigious journals such as Journal of the American Statistical Association, The Annals of Statistics and IEEE Network.

In The Last Decade

James C. Fu

77 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James C. Fu Canada 22 844 581 565 499 325 81 2.0k
Markos V. Koutras Greece 26 1.2k 1.5× 625 1.1× 677 1.2× 749 1.5× 505 1.6× 107 2.4k
Perwez Shahabuddin United States 26 519 0.6× 193 0.3× 262 0.5× 180 0.4× 1.1k 3.3× 61 2.7k
J. D. Esary United States 15 1.1k 1.3× 274 0.5× 786 1.4× 551 1.1× 903 2.8× 22 2.2k
Thomas H. Savits United States 22 1.5k 1.8× 217 0.4× 1.1k 1.9× 579 1.2× 663 2.0× 80 2.4k
James Lynch United States 14 362 0.4× 117 0.2× 218 0.4× 216 0.4× 212 0.7× 48 1.1k
Henry W. Block United States 23 1.7k 2.0× 289 0.5× 894 1.6× 626 1.3× 751 2.3× 66 2.3k
Bruno Tuffin France 22 331 0.4× 136 0.2× 206 0.4× 286 0.6× 556 1.7× 120 1.6k
Ilya Gertsbakh Israel 22 665 0.8× 104 0.2× 903 1.6× 545 1.1× 200 0.6× 91 1.7k
Min‐Te Chao Taiwan 12 567 0.7× 224 0.4× 218 0.4× 208 0.4× 183 0.6× 19 1.0k
Ilkka Norros Finland 25 335 0.4× 184 0.3× 237 0.4× 113 0.2× 279 0.9× 88 3.1k

Countries citing papers authored by James C. Fu

Since Specialization
Citations

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

Fields of papers citing papers by James C. Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James C. Fu. 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 James C. Fu. The network helps show where James C. Fu may publish in the future.

Co-authorship network of co-authors of James C. Fu

This figure shows the co-authorship network connecting the top 25 collaborators of James C. Fu. A scholar is included among the top collaborators of James C. Fu 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 James C. Fu. James C. Fu 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.
2.
Lin, Longting, Christopher Blair, James C. Fu, et al.. (2023). Prior anticoagulation and bridging thrombolysis improve outcomes in patients with atrial fibrillation undergoing endovascular thrombectomy for anterior circulation stroke. Journal of NeuroInterventional Surgery. 15(e3). e433–e437. 5 indexed citations
3.
Fu, James C., et al.. (2022). On Distribution and Average Run Length of a Two-Stage Control Process. Methodology And Computing In Applied Probability. 24(4). 2723–2742. 1 indexed citations
4.
Fu, James C., et al.. (2016). Distributions and Causation Probabilities of Multiple-Run-Rules and Their Applications in System Reliability, Quality Control, and Start-Up Tests. IEEE Transactions on Reliability. 65(3). 1624–1628. 7 indexed citations
5.
Fu, James C., et al.. (2016). On coupon collector’s and Dixie cup problems under fixed and random sample size sampling schemes. Annals of the Institute of Statistical Mathematics. 69(5). 1129–1139. 2 indexed citations
6.
Fu, James C., et al.. (2010). Linear and Nonlinear Boundary Crossing Probabilities for Brownian Motion and Related Processes. Journal of Applied Probability. 47(4). 1058–1071. 16 indexed citations
7.
Fu, James C., et al.. (2009). Approximate probabilities for runs and patterns in i.i.d. and Markov-dependent multistate trials. Advances in Applied Probability. 41(1). 292–308. 9 indexed citations
8.
Fu, James C., et al.. (2009). Approximate probabilities for runs and patterns in i.i.d. and Markov-dependent multistate trials. Advances in Applied Probability. 41(1). 292–308. 1 indexed citations
9.
Eryılmaz, Serkan & James C. Fu. (2007). Runs in continuous-valued sequences. Statistics & Probability Letters. 78(6). 759–765. 2 indexed citations
10.
Wang, Liqun & James C. Fu. (2007). A practical sampling approach for a Bayesian mixture model with unknown number of components. Statistical Papers. 48(4). 631–653. 4 indexed citations
11.
Fu, James C., Liqun Wang, & Wendy Lou. (2003). On exact and large deviation approximation for the distribution of the longest run in a sequence of two-state Markov dependent trials. Journal of Applied Probability. 40(2). 346–360. 31 indexed citations
12.
Fu, James C., Wendy Lou, Zhidong Bai, & Gang Li. (2002). The Exact and Limiting Distributions for the Number of Successes in Success Runs Within a Sequence of Markov-Dependent Two-State Trials. Annals of the Institute of Statistical Mathematics. 54(4). 719–730. 12 indexed citations
13.
Fu, James C., Fred Spiring, & Hansheng Xie. (2002). On the average run lengths of quality control schemes using a Markov chain approach. Statistics & Probability Letters. 56(4). 369–380. 49 indexed citations
14.
Fu, James C.. (2001). Distribution of the scan statistic for a sequence of bistate trials. Journal of Applied Probability. 38(4). 908–916. 34 indexed citations
15.
Fu, James C. & Robert Sproule. (1995). A generalization of the binomial distribution. Communication in Statistics- Theory and Methods. 24(10). 2645–2658. 9 indexed citations
16.
Fu, James C. & Markos V. Koutras. (1994). Distribution Theory of Runs: A Markov Chain Approach. Journal of the American Statistical Association. 89(427). 1050–1058. 299 indexed citations
17.
Fu, James C., et al.. (1990). A NUMERICAL COMPARISON OF NORMAL AND LARGE DEVIATION APPROXIMATION FOR TAIL PROBABILITIES. 20(1). 61–67. 1 indexed citations
18.
Fu, James C., et al.. (1986). On a fundamental optimality of the maximum likelihood estimator. Statistics & Probability Letters. 4(4). 173–178. 4 indexed citations
19.
Fu, James C.. (1975). The Rate of Convergence of Consistent Point Estimators. The Annals of Statistics. 3(1). 18 indexed citations
20.
Fu, James C.. (1974). On Non-Uniqueness of Ancillary Statistics. Communications in Statistics - Simulation and Computation. 3(11). 1093–1100.

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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