Alfredas Račkauskas

750 citations
70 papers · 419 indexed · h-index 12

Alfredas Račkauskas

52 papers receiving 335 citations

Peers

Alfredas Račkauskas
Comparison fields: 5 of 57
  • Finance 204
  • Statistics and Probability 153
  • Mathematical Physics 140
  • Management Science and Operations Research 147
  • Applied Mathematics 62
Replace Marjorie G. Hahn with:
Marjorie G. Hahn United States
Sana Louhichi France
J.M.P. Albin Sweden
M.C.A. van Zuijlen Netherlands
В. А. Волконский Russia
Balram S. Rajput United States
Konstantin Borovkov Australia
Yu. A. Davydov France
P. W. Millar United States
Erich Haeusler Germany
Alfredas Račkauskas relative to Marjorie G. Hahn United States Marjorie G. Hahn's profile →
Citations per field
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Marjorie G. Hahn · 1×
Citations per year

Countries citing papers authored by Alfredas Račkauskas

Since Specialization
Citations

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

Fields of papers citing papers by Alfredas Račkauskas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alfredas Račkauskas. 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 Alfredas Račkauskas. The network helps show where Alfredas Račkauskas may publish in the future.

Co-authorship network

The 8 scholars most cited alongside Alfredas Račkauskas, 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 Alfredas Račkauskas Line = papers co-authored together Alfredas Račkauskas links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20230
2 20200
3 20191
4 20148
5 20134
6 20118
7 201013
8 201010
9 20075
10 20061
11 20054
12 20033
13
Functional Data Analysis of Payment Systems
200218
14 200119
15 200021
16 19961
17 19846
18 19841
19 19841
20 19801

About Alfredas Račkauskas

Alfredas Račkauskas is a scholar working on Mathematical Physics, Finance and Statistics and Probability, having authored 70 papers that have together received 419 indexed citations. Recurring topics across this work include Probability and Risk Models (25 papers), Stochastic processes and financial applications (24 papers), Stochastic processes and statistical mechanics (15 papers), Bayesian Methods and Mixture Models (12 papers), Statistical Methods and Inference (12 papers), Financial Risk and Volatility Modeling (12 papers), advanced mathematical theories (8 papers) and Advanced Banach Space Theory (7 papers). The work is most often cited by research in Finance (204 citations), Statistics and Probability (153 citations) and Mathematical Physics (140 citations). Alfredas Račkauskas has collaborated with scholars based in Lithuania, France and Denmark. Frequent co-authors include V. Bentkus, Vygantas Paulauskas, Yu. I. Davydov, Virmantas Kvedaras, Thomas Mikosch, Rimas Norvaiša, Mindaugas Bloznelis and Remigijus Leipus. Their work appears in journals such as SHILAP Revista de lepidopterología, European Journal of Operational Research and Probability Theory and Related Fields.

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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