D. R. Cox

38 papers receiving 2.3k citations

Hit Papers

A General Definition of Residuals19682026198720061968250500750

Peers

D. R. Cox
Comparison fields: 5 of 186
  • Statistics and Probability 1.3k
  • Statistics, Probability and Uncertainty 344
  • Economics and Econometrics 327
  • Artificial Intelligence 289
  • Management Science and Operations Research 289
Replace Norman L. Johnson with:
Norman L. Johnson United States
Richard A. Groeneveld United States
Diane Lambert United States
Gordon V. Kass South Africa
George Casella United States
G. À. Whitmore Canada
Robert Schlaifer United States
I. Richard Savage United States
Harry V. Roberts United States
Edward Greenberg United States
D. R. Cox relative to Norman L. Johnson United States Norman L. Johnson's profile →
Citations per field
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Norman L. Johnson · 1×
Citations per year

Countries citing papers authored by D. R. Cox

Since Specialization
Citations

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

Fields of papers citing papers by D. R. Cox

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. R. Cox

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 3
2
Design of investigations, statistical methods and applications
0
3
Foundations of statistical inference, theoretical statistics, time series and stochastic processes
0
4 61
5
The theory of stochastic processes / D.R. Cox, H.D. Miller
1
6 45
7 31
8 5
9 13
10 7
11 1
12 1
13 362
14 60
15 54
16 68
17 337
18 13
19 30
20 108

About D. R. Cox

D. R. Cox is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Management Science and Operations Research, having authored 41 papers that have together received 2.6k indexed citations. Recurring topics across this work include Statistical Distribution Estimation and Applications (14 papers), Statistical Methods and Bayesian Inference (6 papers) and Probabilistic and Robust Engineering Design (5 papers). The work is most often cited by research in Statistics and Probability (1.3k citations), Statistics, Probability and Uncertainty (344 citations) and Management Science and Operations Research (289 citations). D. R. Cox has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include E. J. Snell, Valerie Isham, Nanny Wermuth, Ole E. Barndorff–Nielsen, Ian Diamond, Graham F. Medley, P. J. Solomon, A. C. Davison, Christiana Kartsonaki and Agnes M. Herzberg. Their work appears in journals such as Technometrics, Biometrika and Journal of the Royal Statistical Society Series B (Statistical Methodology).

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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