D. E. Amos

1.7k citations
70 papers · 1.2k indexed · h-index 17

D. E. Amos

67 papers receiving 1.1k citations

Peers

D. E. Amos
Comparison fields: 5 of 93
  • Statistics and Probability 167
  • Applied Mathematics 171
  • Modeling and Simulation 60
  • Numerical Analysis 69
  • Mathematical Physics 107
Replace R. V. Churchill with:
R. V. Churchill United States
Ned Anderson United States
Gustav Doetsch Germany
Aldo Tagliani Italy
Serge Dubuc Canada
E.E. Lewis United States
Seymour Haber United States
H. Schwetlick Germany
R. M. Redheffer United States
A. V. Balakrishnan
D. E. Amos relative to R. V. Churchill United States R. V. Churchill's profile →
Citations per field
00.5×4.4×
R. V. Churchill · 1×
Citations per year

Countries citing papers authored by D. E. Amos

Since Specialization
Citations

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

Fields of papers citing papers by D. E. Amos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. E. Amos. 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 D. E. Amos. The network helps show where D. E. Amos may publish in the future.

Co-authorship network

The 25 scholars most cited alongside D. E. Amos, 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 D. E. Amos Line = papers co-authored together D. E. Amos links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201710
2 201614
3 200819
4 200438
5 1991104
6
Estimation of particle-size distributions
19821
7 198025
8 197725
9 19763
10 1974127
11 19738
12 19733
13 197210
14 19721
15 196912
16 19692
17 19693
18 19693
19 19697
20 196420

About D. E. Amos

D. E. Amos is a scholar working on Numerical Analysis, Statistics and Probability, Theoretical Computer Science, Applied Mathematics and Mathematical Physics, having authored 70 papers that have together received 1.2k indexed citations. Recurring topics across this work include Heat Transfer and Optimization (13 papers), Mathematical functions and polynomials (9 papers), Bayesian Methods and Mixture Models (8 papers), Statistical Distribution Estimation and Applications (8 papers), Thermal properties of materials (5 papers), Numerical methods in inverse problems (5 papers), Polynomial and algebraic computation (4 papers) and Matrix Theory and Algorithms (4 papers). The work is most often cited by research in Statistics and Probability (167 citations), Applied Mathematics (171 citations), Modeling and Simulation (60 citations), Numerical Analysis (69 citations) and Mathematical Physics (107 citations). D. E. Amos has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include James V. Beck, V.K. Luk, Filippo de Monte, A. Haji‐Sheikh, M. J. Forrestal, E. S. Pearson, Norman L. Johnson, William G. Bulgren, Robert L. McMasters and A. D. Romig. Their work appears in journals such as ACM Transactions on Mathematical Software, International Journal of Heat and Mass Transfer, Mathematics of Computation, Journal of Applied Mechanics and Journal of the American Statistical Association.

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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