Min‐Te Chao

1.5k citations
19 papers · 1.0k indexed · h-index 12

Impact in

Papers in

Min‐Te Chao

19 papers receiving 927 citations

Peers

Min‐Te Chao
Comparison fields: 5 of 99
  • Statistics and Probability 567
  • Statistics, Probability and Uncertainty 208
  • Safety, Risk, Reliability and Quality 218
  • Software 80
  • Management Science and Operations Research 183
Replace Erwin Straub with:
Erwin Straub Switzerland
Fabio Spizzichino Italy
James C. Fu Canada
Jayaram Sethuraman United States
S. N. U. A. Kirmani United States
R.Y. Rubinstein Israel
Z. A. Łomnicki China
Marvin K. Nakayama United States
B. K. Ghosh United States
Jie Mi United States
Min‐Te Chao relative to Erwin Straub Switzerland Erwin Straub's profile →
Citations per field
00.5×1.5×1.9×
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 1972315
2 1995170
3 197287
4 198284
5 198956
6 199150
7 199647
8 197843
9 199139
10 198438
11 198833
12 199519
13 197811
14 200811
15
BOOTSTRAP METHODS FOR THE UP AND DOWN TEST ON PYROTECHNICS SENSITIVITY ANALYSIS
20016
16 19935
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, Software, Safety, Risk, Reliability and Quality and Finance, having authored 19 papers that have together received 1.0k indexed citations. Recurring topics across this work include Advanced Statistical Process Monitoring (6 papers), Advanced Statistical Methods and Models (6 papers), Statistical Methods and Inference (5 papers), Statistical Distribution Estimation and Applications (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 (567 citations), Statistics, Probability and Uncertainty (208 citations), Safety, Risk, Reliability and Quality (218 citations), Software (80 citations) and Management Science and Operations Research (183 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, Advances in Applied Probability, IEEE Transactions on Reliability, The Annals of Statistics and Propellants Explosives Pyrotechnics.

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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2026