T.A. Yancey
- Statistics and Probability top 1%
- Economics and Econometrics top 10%
- Statistics, Probability and Uncertainty top 5%
- Management Science and Operations Research top 10%
- General Economics, Econometrics and Finance top 10%
- Co-authors
- George G. JudgeMary Ellen BockAman UllahRobert BohrerDavid M. MandyGang YiTimo TeräsvirtaDudley J. Cowden
- Topics
- Advanced Statistical Methods and Models (19 papers)Advanced Statistical Process Monitoring (8 papers)Statistical Methods and Inference (7 papers)
- Cited by
- Statistics and ProbabilityStatistics, Probability and UncertaintyGeneral Economics, Econometrics and Finance
- Journals
- Journal of the American Statistical AssociationEconometricaThe Review of Economics and Statistics
- Partner nations
- United StatesFinland
In The Last Decade
T.A. Yancey
32 papers receiving 372 citations
Peers
Comparison fields: 5 of 58
- Statistics and Probability 300
- Economics and Econometrics 71
- Statistics, Probability and Uncertainty 68
- Management Science and Operations Research 66
- General Economics, Econometrics and Finance 55
Countries citing papers authored by T.A. Yancey
This map shows the geographic impact of T.A. Yancey'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 T.A. Yancey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T.A. Yancey more than expected).
Fields of papers citing papers by T.A. Yancey
This network shows the impact of papers produced by T.A. Yancey. 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 T.A. Yancey. The network helps show where T.A. Yancey may publish in the future.
Co-authorship network of co-authors of T.A. Yancey
This figure shows the co-authorship network connecting the top 25 collaborators of T.A. Yancey. A scholar is included among the top collaborators of T.A. Yancey 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 T.A. Yancey. T.A. Yancey is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | The risk properties of a pre-test estimator for Zellner's seemingly unrelated regression model | 1 |
| 2 | 1 | |
| 3 | 10 | |
| 4 | 65 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 27 | |
| 9 | 16 | |
| 10 | 17 | |
| 11 | 21 | |
| 12 | 68 | |
| 13 | 19 | |
| 14 | 12 | |
| 15 | 19 | |
| 16 | 6 | |
| 17 | 3 | |
| 18 | 5 | |
| 19 | 22 | |
| 20 | 16 |
About T.A. Yancey
T.A. Yancey is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Management Science and Operations Research, having authored 33 papers that have together received 451 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (19 papers), Advanced Statistical Process Monitoring (8 papers) and Statistical Methods and Inference (7 papers). The work is most often cited by research in Statistics and Probability (300 citations), Statistics, Probability and Uncertainty (68 citations) and General Economics, Econometrics and Finance (55 citations). T.A. Yancey has collaborated with scholars based in United States and Finland. Frequent co-authors include George G. Judge, Mary Ellen Bock, Aman Ullah, Robert Bohrer, David M. Mandy, Gang Yi, Timo Teräsvirta, Dudley J. Cowden and Anil K. Bera. Their work appears in journals such as Journal of the American Statistical Association, Econometrica and The Review of Economics and Statistics.
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.