De-Min Wu

1.9k total citations · 1 hit paper
11 papers, 1.2k citations indexed

About

De-Min Wu is a scholar working on Statistics and Probability, Applied Mathematics and Environmental Engineering. According to data from OpenAlex, De-Min Wu has authored 11 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Statistics and Probability, 2 papers in Applied Mathematics and 2 papers in Environmental Engineering. Recurrent topics in De-Min Wu's work include Advanced Statistical Methods and Models (6 papers), Statistical Methods and Inference (3 papers) and Statistical and numerical algorithms (2 papers). De-Min Wu is often cited by papers focused on Advanced Statistical Methods and Models (6 papers), Statistical Methods and Inference (3 papers) and Statistical and numerical algorithms (2 papers). De-Min Wu collaborates with scholars based in United States and China. De-Min Wu's co-authors include David H. Richardson, Yang Shi, Jinghan Wang, Liang Qiao, Wei Gan, Xiaoqing Jiang, Qing Ouyang, Feiling Feng, Qingbao Cheng and Boyi Liao and has published in prestigious journals such as Journal of the American Statistical Association, Econometrica and Frontiers in Oncology.

In The Last Decade

De-Min Wu

11 papers receiving 1.1k citations

Hit Papers

Alternative Tests of Independence between Stochastic Regr... 1973 2026 1990 2008 1973 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
De-Min Wu United States 10 597 256 250 193 180 11 1.2k
Terry G. Seaks United States 12 526 0.9× 161 0.6× 155 0.6× 128 0.7× 70 0.4× 28 1.0k
Richard W. Parks United States 15 1.3k 2.1× 514 2.0× 191 0.8× 264 1.4× 54 0.3× 26 1.8k
Vassilis A. Hajivassiliou United States 10 661 1.1× 171 0.7× 73 0.3× 183 0.9× 149 0.8× 17 1.1k
Vincenzo Verardi Belgium 16 419 0.7× 162 0.6× 156 0.6× 96 0.5× 93 0.5× 43 970
Gabriel Montes‐Rojas United States 20 911 1.5× 285 1.1× 218 0.9× 216 1.1× 164 0.9× 108 1.4k
Seung C. Ahn United States 16 1.5k 2.6× 726 2.8× 188 0.8× 468 2.4× 259 1.4× 41 2.2k
Ben Zipperer United States 8 866 1.5× 151 0.6× 333 1.3× 173 0.9× 59 0.3× 18 1.4k
Ivan A. Canay United States 12 790 1.3× 220 0.9× 88 0.4× 104 0.5× 389 2.2× 27 1.4k
Alan D. Woodland Australia 25 1.5k 2.6× 650 2.5× 210 0.8× 86 0.4× 38 0.2× 82 1.9k
Jan F. Kiviet Netherlands 20 1.9k 3.1× 910 3.6× 242 1.0× 518 2.7× 263 1.5× 57 2.7k

Countries citing papers authored by De-Min Wu

Since Specialization
Citations

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

Fields of papers citing papers by De-Min Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by De-Min Wu. 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 De-Min Wu. The network helps show where De-Min Wu may publish in the future.

Co-authorship network of co-authors of De-Min Wu

This figure shows the co-authorship network connecting the top 25 collaborators of De-Min Wu. A scholar is included among the top collaborators of De-Min Wu 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 De-Min Wu. De-Min Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
Gan, Wei, Liang Qiao, Cheng Ye, et al.. (2021). A New Prognostic Algorithm Predicting HCC Recurrence in Patients With Barcelona Clinic Liver Cancer Stage B Who Received PA-TACE. Frontiers in Oncology. 11. 742630–742630. 10 indexed citations
2.
Ouyang, Qing, Qingbao Cheng, Jinghan Wang, et al.. (2018). Phenformin inhibits cell proliferation and induces cell apoptosis and autophagy in cholangiocarcinoma. Molecular Medicine Reports. 15 indexed citations
3.
Wu, De-Min. (1983). Tests of Causality, Predeterminedness and Exogeneity. International Economic Review. 24(3). 547–547. 16 indexed citations
4.
Wu, De-Min. (1983). A remark on a generalized specification test. Economics Letters. 11(4). 365–370. 11 indexed citations
5.
Wu, De-Min. (1975). Estimation of the Cobb-Douglas Production Function. Econometrica. 43(4). 739–739. 5 indexed citations
6.
Wu, De-Min. (1974). Alternative Tests of Independence between Stochastic Regressors and Disturbances: Finite Sample Results. Econometrica. 42(3). 529–529. 214 indexed citations
7.
Wu, De-Min. (1973). Alternative Tests of Independence between Stochastic Regressors and Disturbances. Econometrica. 41(4). 733–733. 843 indexed citations breakdown →
8.
Richardson, David H. & De-Min Wu. (1971). A Note on the Comparison of Ordinary and Two-Stage Least Squares Estimators. Econometrica. 39(6). 973–973. 24 indexed citations
9.
Richardson, David H. & De-Min Wu. (1970). Least Squares and Grouping Method Estimators in the Errors in Variables Model. Journal of the American Statistical Association. 65(330). 724–748. 60 indexed citations
10.
Richardson, David H. & De-Min Wu. (1970). Least Squares and Grouping Method Estimators in the Errors in Variables Model. Journal of the American Statistical Association. 65(330). 724–724. 18 indexed citations
11.
Wu, De-Min. (1965). An Empirical Analysis of Household Durable Goods Expenditure. Econometrica. 33(4). 761–761. 14 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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