S. T. Boris Choy

1.5k total citations
55 papers, 1.1k citations indexed

About

S. T. Boris Choy is a scholar working on Statistics and Probability, Finance and Artificial Intelligence. According to data from OpenAlex, S. T. Boris Choy has authored 55 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Statistics and Probability, 14 papers in Finance and 13 papers in Artificial Intelligence. Recurrent topics in S. T. Boris Choy's work include Statistical Distribution Estimation and Applications (17 papers), Financial Risk and Volatility Modeling (13 papers) and Bayesian Methods and Mixture Models (12 papers). S. T. Boris Choy is often cited by papers focused on Statistical Distribution Estimation and Applications (17 papers), Financial Risk and Volatility Modeling (13 papers) and Bayesian Methods and Mixture Models (12 papers). S. T. Boris Choy collaborates with scholars based in Australia, Hong Kong and United States. S. T. Boris Choy's co-authors include Jennifer Chan, Philip Beale, Stephen Clarke, Jane Read, Tongwei Qiu, A. F. M. Smith, Biliang Luo, Qinying He, Richard Gerlach and Yifei Li and has published in prestigious journals such as European Journal of Operational Research, British Journal of Cancer and Journal of the Royal Statistical Society Series B (Statistical Methodology).

In The Last Decade

S. T. Boris Choy

52 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S. T. Boris Choy Australia 19 289 188 162 147 142 55 1.1k
Shakeeb Khan United States 20 527 1.8× 37 0.2× 36 0.2× 13 0.1× 46 0.3× 50 1.2k
Thomas Louis United States 18 344 1.2× 117 0.6× 199 1.2× 6 0.0× 81 0.6× 28 2.1k
Amy Racine-Poon Switzerland 15 800 2.8× 22 0.1× 68 0.4× 9 0.1× 292 2.1× 24 1.8k
Giovanni De Luca Italy 17 55 0.2× 11 0.1× 203 1.3× 20 0.1× 47 0.3× 81 715
Bruce L. Jones Canada 16 164 0.6× 48 0.3× 204 1.3× 8 0.1× 19 0.1× 54 761
Halina Frydman United States 17 297 1.0× 9 0.0× 359 2.2× 8 0.1× 202 1.4× 44 1.1k
Kimberly F. Sellers United States 14 360 1.2× 68 0.4× 19 0.1× 2 0.0× 170 1.2× 42 986
Anabel Forte Spain 13 176 0.6× 37 0.2× 47 0.3× 12 0.1× 71 0.5× 39 777
Anton Abdulbasah Kamil Malaysia 15 19 0.1× 11 0.1× 83 0.5× 62 0.4× 31 0.2× 125 834
Filippo Domma Italy 16 317 1.1× 47 0.3× 98 0.6× 3 0.0× 40 0.3× 40 602

Countries citing papers authored by S. T. Boris Choy

Since Specialization
Citations

This map shows the geographic impact of S. T. Boris Choy'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 S. T. Boris Choy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. T. Boris Choy more than expected).

Fields of papers citing papers by S. T. Boris Choy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. T. Boris Choy. 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 S. T. Boris Choy. The network helps show where S. T. Boris Choy may publish in the future.

Co-authorship network of co-authors of S. T. Boris Choy

This figure shows the co-authorship network connecting the top 25 collaborators of S. T. Boris Choy. A scholar is included among the top collaborators of S. T. Boris Choy 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 S. T. Boris Choy. S. T. Boris Choy 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.
Trafimow, David, Tingting Tong, S. T. Boris Choy, et al.. (2024). Improving inferential analyses predata and postdata.. Psychological Methods. 2 indexed citations
2.
Hu, Liqun, et al.. (2023). Extending the A Priori Procedure (APP) to Analysis of Variance Models under Normality. Axioms. 13(1). 22–22. 1 indexed citations
3.
Trafimow, David, Tingting Tong, Tonghui Wang, et al.. (2023). Surprising implications of differences in locations versus differences in means. Methodology. 19(2). 152–169. 1 indexed citations
4.
Zhu, Xiaonan, Zheng Wei, Tonghui Wang, S. T. Boris Choy, & Ziwei Ma. (2023). An expectation conditional maximization algorithm for the skew-normal based stochastic frontier model. Computational Statistics. 39(3). 1539–1558. 1 indexed citations
5.
Qiu, Tongwei, Xianlei Ma, Luo Bi-liang, S. T. Boris Choy, & Qinying He. (2022). Land defragmentation in China: does rental transaction inside acquaintance networks matter?. Journal of Applied Economics. 25(1). 260–279. 3 indexed citations
6.
Gao, Junbin, et al.. (2021). Coupling matrix manifolds assisted optimization for optimal transport problems. Machine Learning. 110(3). 533–558. 3 indexed citations
7.
Qiu, Tongwei, Luo Bi-liang, S. T. Boris Choy, Xianlei Ma, & Qinying He. (2020). The demonstration effect of transactions between strangers on those between acquaintances: evidence from land rentals in rural China. Applied Economics. 52(43). 4780–4793. 14 indexed citations
8.
Qiu, Tongwei, et al.. (2019). Does land renting-in reduce grain production? Evidence from rural China. Land Use Policy. 90. 104311–104311. 62 indexed citations
9.
Lam, Yeh, S. T. Boris Choy, & Philip L. H. Yu. (2016). A sequential sampling plan for exponential distribution. Sequential Analysis. 35(3). 331–346. 1 indexed citations
10.
Choy, S. T. Boris, Jennifer Chan, & Udi Makov. (2015). Robust Bayesian analysis of loss reserving data using scale mixtures distributions. Journal of Applied Statistics. 43(3). 396–411. 4 indexed citations
11.
Choy, S. T. Boris, et al.. (2014). Analyzing return asymmetry and quantiles through stochastic volatility models using asymmetric Laplace error via uniform scale mixtures. Applied Stochastic Models in Business and Industry. 31(5). 584–608. 9 indexed citations
12.
Choy, S. T. Boris, et al.. (2014). A generalized class of skew distributions and associated robust quantile regression models. Canadian Journal of Statistics. 42(4). 579–596. 32 indexed citations
13.
Chan, Jennifer, S. T. Boris Choy, & Connie Lam. (2014). Modeling Electricity Price Using A Threshold Conditional Autoregressive Geometric Process Jump Model. Communication in Statistics- Theory and Methods. 43(10-12). 2505–2515. 13 indexed citations
14.
Chan, Jennifer, S. T. Boris Choy, & Udi Makov. (2008). Robust Bayesian Analysis of Loss Reserves Data Using the Generalized-tDistribution. Astin Bulletin. 38(1). 207–230. 11 indexed citations
15.
Read, Jane, S. T. Boris Choy, Philip Beale, & Stephen Clarke. (2006). Evaluation of Nutritional and Inflammatory Status of Advanced Colorectal Cancer Patients and Its Correlation With Survival. Nutrition and Cancer. 55(1). 78–85. 135 indexed citations
16.
17.
Choy, S. T. Boris, et al.. (2005). The Pre- and Post-1997 Well-Being of Hong Kong Residents. Social Indicators Research. 71(1-3). 231–258. 4 indexed citations
18.
Woo, Pauline, TQ Thach, S. T. Boris Choy, S M McGhee, & GM Leung. (2005). Modelling the impact of population-based cytologic screening on cervical cancer incidence and mortality in Hong Kong: an age–period–cohort approach. British Journal of Cancer. 93(9). 1077–1083. 9 indexed citations
19.
Choy, S. T. Boris & Chun Man Chan. (2000). BAYESIAN ESTIMATION OF STOCHASTIC VOLATILITY MODEL VIA SCALE MIXTURES DISTRIBUTIONS. 185–204. 3 indexed citations
20.
Choy, S. T. Boris & A. F. M. Smith. (1997). Hierarchical models with scale mixtures of normal distributions. Test. 6(1). 205–221. 49 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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