Wing K. Fung

2.6k total citations
139 papers, 1.7k citations indexed

About

Wing K. Fung is a scholar working on Statistics and Probability, Genetics and Molecular Biology. According to data from OpenAlex, Wing K. Fung has authored 139 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Statistics and Probability, 60 papers in Genetics and 31 papers in Molecular Biology. Recurrent topics in Wing K. Fung's work include Advanced Statistical Methods and Models (43 papers), Statistical Methods and Inference (33 papers) and Statistical Methods and Bayesian Inference (31 papers). Wing K. Fung is often cited by papers focused on Advanced Statistical Methods and Models (43 papers), Statistical Methods and Inference (33 papers) and Statistical Methods and Bayesian Inference (31 papers). Wing K. Fung collaborates with scholars based in Hong Kong, China and United States. Wing K. Fung's co-authors include Zhongyi Zhu, Xuming He, Yue‐Qing Hu, Xuming He, Bo Fu, Ji‐Yuan Zhou, Andy H. Lee, Jun Chen, Hongzhe Li and Fan Dora Xia and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Bioinformatics.

In The Last Decade

Wing K. Fung

135 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wing K. Fung Hong Kong 22 796 447 276 227 144 139 1.7k
Dan Lin United States 24 572 0.7× 431 1.0× 572 2.1× 206 0.9× 46 0.3× 79 2.0k
Helena Geys Belgium 25 944 1.2× 84 0.2× 210 0.8× 108 0.5× 114 0.8× 93 2.1k
Chris J. Lloyd Australia 23 621 0.8× 86 0.2× 416 1.5× 173 0.8× 201 1.4× 134 1.8k
Greg C. G. Wei United States 10 600 0.8× 65 0.1× 84 0.3× 341 1.5× 65 0.5× 21 1.1k
Jianguo Sun United States 30 3.0k 3.8× 140 0.3× 145 0.5× 700 3.1× 205 1.4× 243 3.7k
Gregg E. Dinse United States 21 547 0.7× 85 0.2× 176 0.6× 106 0.5× 76 0.5× 57 1.4k
Daowen Zhang United States 23 737 0.9× 351 0.8× 207 0.8× 239 1.1× 40 0.3× 50 1.9k
Jacobo de Uña‐Álvarez Spain 20 876 1.1× 94 0.2× 122 0.4× 287 1.3× 81 0.6× 94 1.6k
Beat Neuenschwander Switzerland 22 1.5k 1.9× 143 0.3× 227 0.8× 73 0.3× 314 2.2× 44 2.4k
Wei Tan United States 21 299 0.4× 156 0.3× 616 2.2× 75 0.3× 44 0.3× 118 1.6k

Countries citing papers authored by Wing K. Fung

Since Specialization
Citations

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

Fields of papers citing papers by Wing K. Fung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wing K. Fung. 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 Wing K. Fung. The network helps show where Wing K. Fung may publish in the future.

Co-authorship network of co-authors of Wing K. Fung

This figure shows the co-authorship network connecting the top 25 collaborators of Wing K. Fung. A scholar is included among the top collaborators of Wing K. Fung 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 Wing K. Fung. Wing K. Fung 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.
Wang, Peng, et al.. (2022). A Novel Penalized Inverse-Variance Weighted Estimator for Mendelian Randomization with Applications to COVID-19 Outcomes. Biometrics. 79(3). 2184–2195. 18 indexed citations
2.
Zhang, Yu, et al.. (2022). BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation. BMC Bioinformatics. 23(1). 193–193. 1 indexed citations
3.
Li, Jianlong, et al.. (2018). A powerful parent-of-origin effects test for qualitative traits on X chromosome in general pedigrees. BMC Bioinformatics. 19(1). 8–8. 2 indexed citations
4.
Yu, Kexin, Ji‐Yuan Zhou, & Wing K. Fung. (2017). Detection of Imprinting Effects for Quantitative Traits on X Chromosome Using Nuclear Families with Multiple Daughters. Annals of Human Genetics. 81(4). 147–160. 1 indexed citations
5.
Zhou, Ji‐Yuan, et al.. (2013). Powerful tests for association on quantitative trait loci incorporating imprinting effects. Journal of Human Genetics. 58(6). 384–390. 2 indexed citations
6.
Fung, Wing K., et al.. (2012). Simple Algorithms to Calculate Asymptotic Null Distributions of Robust Tests in Case-Control Genetic Association Studies in R. SHILAP Revista de lepidopterología. 2 indexed citations
7.
Zang, Yong & Wing K. Fung. (2011). Robust Mantel-Haenszel test under genetic model uncertainty allowing for covariates in case-control association studies. Genetic Epidemiology. 35(7). 695–705. 7 indexed citations
8.
Yang, Chi‐Ting, et al.. (2010). Population pharmacokinetics of alcohol on Chinese subjects using breath measures. Journal of Clinical Pharmacy and Therapeutics. 36(6). 716–724. 3 indexed citations
9.
Fung, Wing K., et al.. (2008). Penalized quadratic inference functions for single-index models with longitudinal data. Journal of Multivariate Analysis. 100(1). 152–161. 42 indexed citations
10.
Fung, Wing K., et al.. (2007). Structural Parameter Estimation Using Generalized Estimating Equations for Regression Credibility Models. Astin Bulletin. 37(2). 323–343. 3 indexed citations
11.
Guo, Wei & Wing K. Fung. (2005). Combining the case–control methodology with the small size transmission/disequilibrium test for multiallelic markers. European Journal of Human Genetics. 13(9). 1007–1012. 6 indexed citations
12.
Chan, Karen M. K., et al.. (2004). Population data for the Identifier™ 15 STR loci in Hong Kong Chinese. Forensic Science International. 152(2-3). 307–309. 13 indexed citations
13.
Fung, Wing K. & Yue‐Qing Hu. (2001). The evaluation of mixed stains from different ethnic origins: general result and common cases. International Journal of Legal Medicine. 115(1). 48–53. 5 indexed citations
14.
He, Xuming & Wing K. Fung. (2000). High Breakdown Estimation for Multiple Populations with Applications to Discriminant Analysis. Journal of Multivariate Analysis. 72(2). 151–162. 74 indexed citations
15.
Fung, Wing K.. (1998). On the equivalence of two diagnostic measures in discriminant analysis. Communication in Statistics- Theory and Methods. 27(8). 1915–1922. 2 indexed citations
16.
Fung, Wing K., et al.. (1997). Further influence measures in factor analysis. Communication in Statistics- Theory and Methods. 26(6). 1337–1353. 1 indexed citations
17.
Fung, Wing K.. (1996). Are convenience DNA samples significantly different?. Forensic Science International. 82(3). 233–241. 2 indexed citations
18.
Fung, Wing K.. (1995). Graphical summaries for influence of multiple observations. Communication in Statistics- Theory and Methods. 24(2). 415–427. 2 indexed citations
19.
Fung, Wing K.. (1995). Diagnostics in Linear Discriminant Analysis. Journal of the American Statistical Association. 90(431). 952–956. 34 indexed citations
20.
Fung, Wing K., et al.. (1987). A New Graphical Method for Detecting Single and Multiple Outliers in Univariate and Multivariate Data. Journal of the Royal Statistical Society Series A (Statistics in Society). 20 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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