Journal of the Royal Statistical Society Series C (Applied Statistics)

153.0k citations
3.3k papers · · active since 2016

Impact in

    • Statistical Methods and Bayesian Inference
    • Statistical Methods and Inference
    • Advanced Statistical Methods and Models
    • Statistical Distribution Estimation and Applications
    • Statistical Methods in Clinical Trials
    • Advanced Statistical Process Monitoring

Papers in

    • Statistical Methods and Bayesian Inference 409
    • Statistical Methods and Inference 395
    • Advanced Statistical Methods and Models 358
    • Statistical Methods in Clinical Trials 226
    • Statistical Distribution Estimation and Applications 122
    • Advanced Statistical Process Monitoring 166

Journal of the Royal Statistical Society Series C (Applied Statistics)

2.4k papers receiving 100.7k citations

Peers

Journal of the Royal Statistical Society Series C (Applied Statistics)
Comparison fields: 5 of 248
  • Statistics and Probability 36.1k
  • Statistics, Probability and Uncertainty 10.4k
  • Management Science and Operations Research 13.8k
  • Artificial Intelligence 23.5k
  • Global and Planetary Change 11.5k
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Journal of the Royal Statistical Society Series C (Applied Statistics) relative to The American Statistician United States The American Statistician's profile →
Citations per field
00.5×1.5×
The American Statistician · 1×
Citations per year

Countries where authors publish in Journal of the Royal Statistical Society Series C (Applied Statistics)

Since Specialization
Citations

This map shows the geographic impact of research published in Journal of the Royal Statistical Society Series C (Applied Statistics). 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 papers published in Journal of the Royal Statistical Society Series C (Applied Statistics) with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Journal of the Royal Statistical Society Series C (Applied Statistics) more than expected).

Fields of papers published in Journal of the Royal Statistical Society Series C (Applied Statistics)

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Journal of the Royal Statistical Society Series C (Applied Statistics). Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Journal of the Royal Statistical Society Series C (Applied Statistics).

About Journal of the Royal Statistical Society Series C (Applied Statistics)

The 3.3k papers published in Journal of the Royal Statistical Society Series C (Applied Statistics) in the last decades have received a total of 153.0k indexed citations . Papers published in Journal of the Royal Statistical Society Series C (Applied Statistics) usually cover Statistics and Probability (1.1k papers), Statistics, Probability and Uncertainty (268 papers), Management Science and Operations Research (359 papers), Artificial Intelligence (481 papers) and Economics and Econometrics (310 papers) specifically the topics of Statistical Methods and Bayesian Inference (409 papers), Statistical Methods and Inference (395 papers), Advanced Statistical Methods and Models (358 papers), Bayesian Methods and Mixture Models (241 papers), Statistical Methods in Clinical Trials (226 papers), Optimal Experimental Design Methods (213 papers), Advanced Statistical Process Monitoring (166 papers) and Statistical Distribution Estimation and Applications (122 papers). The most active scholars publishing in Journal of the Royal Statistical Society Series C (Applied Statistics) are John A. Hartigan, M. Anthony Wong, Anthony N. Pettitt, Gordon V. Kass, Peter John Diggle, Ian T. Jolliffe, J. Patrick Royston, Declan Luke Finney, Dionysios STASINOPOULOS and Robert A. Rigby.

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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