Min‐Te Chao

1.5k citations
19 papers · 1.1k · h-index 13

Impact in

Papers in

Min‐Te Chao

19 papers receiving 1.0k citations

Peers

Min‐Te Chao
Comparison fields: 5 of 99
  • Statistics and Probability 611
  • Statistics, Probability and Uncertainty 226
  • Safety, Risk, Reliability and Quality 237
  • Software 95
  • Management Science and Operations Research 194
Replace Erwin Straub with:
Erwin Straub Switzerland
Fabio Spizzichino Italy
James C. Fu Canada
S. N. U. A. Kirmani United States
Z. A. Łomnicki China
R.Y. Rubinstein Israel
Majid Asadi Iran
António Pacheco Portugal
B. K. Ghosh United States
Jie Mi United States
Min‐Te Chao relative to Erwin Straub Switzerland Erwin Straub's profile →
Citations per field
00.5×1.5×
Erwin Straub · 1×
Citations per year

Countries citing papers authored by Min‐Te Chao

Since Specialization
Citations

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

Fields of papers citing papers by Min‐Te Chao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Min‐Te Chao. 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 Min‐Te Chao. The network helps show where Min‐Te Chao may publish in the future.

Co-authors

The 9 scholars most cited alongside Min‐Te Chao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Min‐Te Chao Line = papers co-authored together Min‐Te Chao links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 1972348
2 1995187
3 198292
4 197287
5 198963
6 199161
7 199649
8 199146
9 198446
10 197845
11 198834
12 199520
13 197812
14 200811
15 19936
16
BOOTSTRAP METHODS FOR THE UP AND DOWN TEST ON PYROTECHNICS SENSITIVITY ANALYSIS
20016
17 19733
18 19862
19 20031

About Min‐Te Chao

Min‐Te Chao is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty, Artificial Intelligence, Safety, Risk, Reliability and Quality and Software, having authored 19 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (6 papers), Advanced Statistical Process Monitoring (6 papers), Statistical Distribution Estimation and Applications (5 papers), Statistical Methods and Inference (5 papers), Reliability and Maintenance Optimization (4 papers), Statistical Methods and Bayesian Inference (4 papers), Bayesian Methods and Mixture Models (4 papers) and Software Reliability and Analysis Research (3 papers). The work is most often cited by research in Statistics and Probability (611 citations), Statistics, Probability and Uncertainty (226 citations), Safety, Risk, Reliability and Quality (237 citations), Software (95 citations) and Management Science and Operations Research (194 citations). Min‐Te Chao has collaborated with scholars based in Taiwan, Canada and United States. Frequent co-authors include Mark Priestley, James C. Fu, Markos V. Koutras, William E. Strawderman, Smiley W. Cheng, Ronald E. Glaser, Shaw‐Hwa Lo, Cheng–Der Fuh and Gwo Dong Lin. Their work appears in journals such as Journal of the American Statistical Association, IEEE Transactions on Reliability, The Annals of Statistics, Advances in Applied Probability and Biometrika.

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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