Ching-Zong Wei

3.1k total citations
29 papers, 1.9k citations indexed

About

Ching-Zong Wei is a scholar working on Statistics and Probability, Finance and Artificial Intelligence. According to data from OpenAlex, Ching-Zong Wei has authored 29 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Statistics and Probability, 11 papers in Finance and 8 papers in Artificial Intelligence. Recurrent topics in Ching-Zong Wei's work include Statistical Methods and Inference (16 papers), Financial Risk and Volatility Modeling (8 papers) and Stochastic processes and financial applications (7 papers). Ching-Zong Wei is often cited by papers focused on Statistical Methods and Inference (16 papers), Financial Risk and Volatility Modeling (8 papers) and Stochastic processes and financial applications (7 papers). Ching-Zong Wei collaborates with scholars based in United States, Taiwan and Austria. Ching-Zong Wei's co-authors include Ngai Hang Chan, Tze Leung Lai, Herbert Robbins, P. Rajesh Kumar, Sangyeol Lee, David F. Findley, Benedikt M. Pötscher, Gopal K. Basak, Inchi Hu and C. K. Chu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Automatic Control and Journal of Econometrics.

In The Last Decade

Ching-Zong Wei

28 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ching-Zong Wei United States 20 822 737 515 451 411 29 1.9k
I. V. Basawa United States 27 1.2k 1.4× 933 1.3× 321 0.6× 363 0.8× 152 0.4× 89 2.0k
Denis Bosq France 14 1.4k 1.7× 775 1.1× 160 0.3× 411 0.9× 281 0.7× 63 2.4k
Elias Masry United States 21 1.0k 1.2× 594 0.8× 170 0.3× 289 0.6× 176 0.4× 64 1.7k
Hira L. Koul United States 29 2.0k 2.4× 1.1k 1.4× 280 0.5× 444 1.0× 132 0.3× 115 2.6k
Sangyeol Lee South Korea 27 1.2k 1.5× 1.2k 1.6× 391 0.8× 606 1.3× 173 0.4× 220 2.4k
Tailen Hsing United States 22 1.1k 1.4× 1.0k 1.4× 151 0.3× 417 0.9× 149 0.4× 61 2.3k
Fabienne Comte France 22 863 1.0× 1.3k 1.8× 238 0.5× 751 1.7× 148 0.4× 96 2.1k
Michael H. Neumann Germany 23 784 1.0× 623 0.8× 177 0.3× 327 0.7× 144 0.4× 58 1.5k
Marie Hušková Czechia 25 1.3k 1.6× 598 0.8× 252 0.5× 396 0.9× 141 0.3× 111 2.0k
Lanh Tat Tran United States 20 928 1.1× 503 0.7× 104 0.2× 317 0.7× 104 0.3× 51 1.4k

Countries citing papers authored by Ching-Zong Wei

Since Specialization
Citations

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

Fields of papers citing papers by Ching-Zong Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching-Zong Wei. 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 Ching-Zong Wei. The network helps show where Ching-Zong Wei may publish in the future.

Co-authorship network of co-authors of Ching-Zong Wei

This figure shows the co-authorship network connecting the top 25 collaborators of Ching-Zong Wei. A scholar is included among the top collaborators of Ching-Zong Wei 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 Ching-Zong Wei. Ching-Zong Wei 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.
Wei, Ching-Zong, et al.. (2005). A new urn model. Journal of Applied Probability. 42(4). 964–976. 23 indexed citations
2.
Wei, Ching-Zong, et al.. (2005). A new urn model. Journal of Applied Probability. 42(4). 964–976. 2 indexed citations
3.
Ing, Ching‐Kang & Ching-Zong Wei. (2005). A maximal moment inequality for long range dependent time series with applications to estimation and model selection. Statistica Sinica. 721–740. 3 indexed citations
4.
Wei, Ching-Zong, et al.. (2003). On same-realization prediction in an infinite-order autoregressive process. Journal of Multivariate Analysis. 85(1). 130–155. 44 indexed citations
5.
Findley, David F. & Ching-Zong Wei. (2002). AIC, Overfitting Principles, and the Boundedness of Moments of Inverse Matrices for Vector Autotregressions and Related Models. Journal of Multivariate Analysis. 83(2). 415–450. 25 indexed citations
6.
Findley, David F., Benedikt M. Pötscher, & Ching-Zong Wei. (2001). Uniform convergence of sample second moments of families of time series arrays. The Annals of Statistics. 29(3). 6 indexed citations
7.
Basak, Gopal K., Inchi Hu, & Ching-Zong Wei. (1997). Weak convergence of recursions. Stochastic Processes and their Applications. 68(1). 65–82. 12 indexed citations
8.
Wei, Ching-Zong & C. K. Chu. (1994). A regression point of view toward density estimation. Journal of nonparametric statistics. 4(2). 191–201. 5 indexed citations
9.
Wei, Ching-Zong. (1993). Martingale transforms with non-atomic limits and stochastic approximation. Probability Theory and Related Fields. 95(1). 103–114. 3 indexed citations
10.
Wei, Ching-Zong. (1992). On Predictive Least Squares Principles. The Annals of Statistics. 20(1). 138 indexed citations
11.
Wei, Ching-Zong, et al.. (1989). Some asymptotic results for the branching process with immigration. Stochastic Processes and their Applications. 31(2). 261–282. 57 indexed citations
12.
Chan, Ngai Hang & Ching-Zong Wei. (1988). Limiting Distributions of Least Squares Estimates of Unstable Autoregressive Processes. The Annals of Statistics. 16(1). 360 indexed citations
13.
Lai, Tze Leung & Ching-Zong Wei. (1987). Asymptotically Efficient Self-Tuning Regulators. SIAM Journal on Control and Optimization. 25(2). 466–481. 28 indexed citations
14.
Lai, Tze Leung & Ching-Zong Wei. (1986). Extended least squares and their applications to adaptive control and prediction in linear systems. IEEE Transactions on Automatic Control. 31(10). 898–906. 123 indexed citations
15.
Kumar, P. Rajesh, et al.. (1985). Adaptive control with the stochastic approximation algorithm: Geometry and convergence. IEEE Transactions on Automatic Control. 30(4). 330–338. 79 indexed citations
16.
Lai, Tze Leung & Ching-Zong Wei. (1983). Asymptotic properties of general autoregressive models and strong consistency of least-squares estimates of their parameters. Journal of Multivariate Analysis. 13(1). 1–23. 93 indexed citations
17.
Lai, Tze Leung & Ching-Zong Wei. (1982). Asymptotic properties of projections with applications to stochastic regression problems. Journal of Multivariate Analysis. 12(3). 346–370. 39 indexed citations
18.
Lai, Tze Leung, et al.. (1981). Convergence systems and strong consistency of least squares estimates in regression models. Journal of Multivariate Analysis. 11(3). 319–333. 37 indexed citations
19.
Lai, Tze Leung, Herbert Robbins, & Ching-Zong Wei. (1979). Strong consistency of least squares estimates in multiple regression II. Journal of Multivariate Analysis. 9(3). 343–361. 147 indexed citations
20.
Lai, Tze Leung, Herbert Robbins, & Ching-Zong Wei. (1978). Strong consistency of least squares estimates in multiple regression. Proceedings of the National Academy of Sciences. 75(7). 3034–3036. 96 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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