Mathematical Methods of Statistics

273 papers and 1.6k indexed citations i.

About

The 273 papers published in Mathematical Methods of Statistics in the last decades have received a total of 1.6k indexed citations. Papers published in Mathematical Methods of Statistics usually cover Statistics and Probability (204 papers), Artificial Intelligence (97 papers) and Finance (66 papers) specifically the topics of Statistical Methods and Inference (138 papers), Bayesian Methods and Mixture Models (81 papers) and Advanced Statistical Methods and Models (57 papers). The most active scholars publishing in Mathematical Methods of Statistics are Salim Bouzebda, Dietrich von Rosen, Yasutaka Shimizu, Yousri Slaoui, Holger Dette, A. B. Tsybakov, Muni S. Srivastava, Oleg Lepski, Sophie Dabo‐Niang and Anne‐Françoise Yao.

In The Last Decade

Fields of papers published in Mathematical Methods of Statistics

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Mathematical Methods of 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 Mathematical Methods of Statistics.

Countries where authors publish in Mathematical Methods of Statistics

Since Specialization
Citations

This map shows the geographic impact of research published in Mathematical Methods of 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 Mathematical Methods of Statistics with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mathematical Methods of Statistics more than expected).

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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