B. S. Everitt

4.0k citations
23 papers · 2.9k indexed · 2 hit papers · h-index 17

B. S. Everitt

23 papers receiving 2.7k citations

Hit Papers

Finite Mixture Distributions76919692026198820074008001.2k

Peers

B. S. Everitt
Comparison fields: 5 of 213
  • Statistics and Probability 714
  • Statistics, Probability and Uncertainty 529
  • Artificial Intelligence 706
  • Family Practice 48
  • Management Science and Operations Research 238
Replace Wayne W. Daniel with:
Wayne W. Daniel United States
Robert J. Beaver United States
Richard M. Royall United States
Donald D. Dorfman United States
Martin T. Wells United States
Helge Toutenburg Germany
David Firth United Kingdom
Alan Kimber United Kingdom
Thomas M. Loughin United States
Lincoln E. Moses United States
B. S. Everitt relative to Wayne W. Daniel United States Wayne W. Daniel's profile →
Citations per field
00.5×3.1×
Wayne W. Daniel · 1×
Citations per year

Countries citing papers authored by B. S. Everitt

Since Specialization
Citations

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

Fields of papers citing papers by B. S. Everitt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by B. S. Everitt. 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 B. S. Everitt. The network helps show where B. S. Everitt may publish in the future.

Co-authorship network

The 12 scholars most cited alongside B. S. Everitt, 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 B. S. Everitt Line = papers co-authored together B. S. Everitt links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1
A Handbook of Statistical Analyses Using SAS [3rd ed.]
20097
2 199942
3 19943
4 199023
5 198914
6 198928
7 198872
8 198831
9 198710
10 198516
11 198442
12 198356
13 198135
14 198177
15 1979249
16 197818
17 197732
18 19723
19
Large sample standard errors of kappa and weighted kappa.breakdown →
19691203
20 1968119

About B. S. Everitt

B. S. Everitt is a scholar working on Statistics and Probability, Artificial Intelligence and Management Science and Operations Research, having authored 23 papers that have together received 2.9k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (6 papers), Advanced Statistical Methods and Models (4 papers), Statistical Distribution Estimation and Applications (3 papers), Advanced Clustering Algorithms Research (3 papers), Statistical Methods and Bayesian Inference (2 papers), Speech and dialogue systems (1 paper), Multi-Criteria Decision Making (1 paper) and Imbalanced Data Classification Techniques (1 paper). The work is most often cited by research in Statistics and Probability (714 citations), Statistics, Probability and Uncertainty (529 citations) and Artificial Intelligence (706 citations). B. S. Everitt has collaborated with scholars based in United Kingdom, United States and Poland. Frequent co-authors include Joseph L. Fleiss, Jacob Cohen, David J. Hand, Jure Zupan, Norma Faris Hubele, Kwan Lee, Sophia Rabe‐Hesketh, Chantal Mérette, H. Späth and Chris Frith. Their work appears in journals such as Biometrics, Multivariate Behavioral Research, Statistical Methods in Medical Research, The British Journal of Psychiatry and Technometrics.

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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