Jonas Šiaulys

854 total citations
100 papers, 584 citations indexed

About

Jonas Šiaulys is a scholar working on Management Science and Operations Research, Finance and Demography. According to data from OpenAlex, Jonas Šiaulys has authored 100 papers receiving a total of 584 indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Management Science and Operations Research, 37 papers in Finance and 31 papers in Demography. Recurrent topics in Jonas Šiaulys's work include Probability and Risk Models (66 papers), Financial Risk and Volatility Modeling (32 papers) and Insurance, Mortality, Demography, Risk Management (31 papers). Jonas Šiaulys is often cited by papers focused on Probability and Risk Models (66 papers), Financial Risk and Volatility Modeling (32 papers) and Insurance, Mortality, Demography, Risk Management (31 papers). Jonas Šiaulys collaborates with scholars based in Lithuania, China and Greece. Jonas Šiaulys's co-authors include Remigijus Leipus, Yang Yang, V. Čekanavičius, Dimitrios G. Konstantinides and Kaiyong Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Mathematical Analysis and Applications and Applied Mathematics and Computation.

In The Last Decade

Jonas Šiaulys

91 papers receiving 539 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jonas Šiaulys Lithuania 14 467 273 224 175 119 100 584
Qingwu Gao China 11 452 1.0× 232 0.8× 202 0.9× 137 0.8× 144 1.2× 42 555
Kaiyong Wang China 14 581 1.2× 314 1.2× 275 1.2× 188 1.1× 167 1.4× 45 594
Philip S. Griffin United States 14 305 0.7× 215 0.8× 43 0.2× 179 1.0× 290 2.4× 46 511
A. V. Nagaev Poland 10 262 0.6× 190 0.7× 46 0.2× 144 0.8× 231 1.9× 53 486
Olof Thorin Sweden 11 246 0.5× 162 0.6× 64 0.3× 189 1.1× 67 0.6× 21 408
Dongya Cheng China 12 342 0.7× 175 0.6× 143 0.6× 135 0.8× 78 0.7× 36 354
Dimitrios G. Konstantinides Greece 11 380 0.8× 209 0.8× 236 1.1× 80 0.5× 95 0.8× 38 437
Harri Nyrhinen Finland 9 362 0.8× 217 0.8× 207 0.9× 91 0.5× 76 0.6× 22 410
Juan Carlos Pardo Mexico 16 299 0.6× 387 1.4× 62 0.3× 125 0.7× 329 2.8× 53 593
Jia-an Yan China 9 259 0.6× 187 0.7× 115 0.5× 50 0.3× 100 0.8× 18 408

Countries citing papers authored by Jonas Šiaulys

Since Specialization
Citations

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

Fields of papers citing papers by Jonas Šiaulys

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonas Šiaulys

This figure shows the co-authorship network connecting the top 25 collaborators of Jonas Šiaulys. A scholar is included among the top collaborators of Jonas Šiaulys 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 Jonas Šiaulys. Jonas Šiaulys 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
1.
Šiaulys, Jonas, et al.. (2024). The Random Effect Transformation for Three Regularity Classes. Mathematics. 12(24). 3932–3932.
2.
Šiaulys, Jonas, et al.. (2024). On the distribution-tail of the product of gamma random variables. Nonlinear Analysis Modelling and Control. 29(6). 1186–1205. 1 indexed citations
3.
Leipus, Remigijus, et al.. (2024). Randomly Stopped Sums, Minima and Maxima for Heavy-Tailed and Light-Tailed Distributions. Axioms. 13(6). 355–355.
4.
Šiaulys, Jonas, et al.. (2024). Randomly Stopped Minimum, Maximum, Minimum of Sums and Maximum of Sums with Generalized Subexponential Distributions. Axioms. 13(2). 85–85. 3 indexed citations
5.
Šiaulys, Jonas, et al.. (2023). Randomly Stopped Sums with Generalized Subexponential Distribution. Axioms. 12(7). 641–641. 3 indexed citations
6.
Leipus, Remigijus, et al.. (2023). On the distribution-tail behaviour of the product of normal random variables. Journal of Inequalities and Applications. 2023(1). 3 indexed citations
7.
Leipus, Remigijus, Jonas Šiaulys, & Dimitrios G. Konstantinides. (2023). Closure Properties for Heavy-Tailed and Related Distributions. 8 indexed citations
8.
Šiaulys, Jonas, et al.. (2023). Ruin probability for renewal risk models with neutral net profit condition. Nonlinear Analysis Modelling and Control. 28(6). 1182–1195. 2 indexed citations
9.
Šiaulys, Jonas, et al.. (2023). Truncated Moments for Heavy-Tailed and Related Distribution Classes. Mathematics. 11(9). 2172–2172. 2 indexed citations
10.
Konstantinides, Dimitrios G., Remigijus Leipus, & Jonas Šiaulys. (2022). On the non-closure under convolution for strong subexponential distributions. Nonlinear Analysis Modelling and Control. 28. 1–19. 3 indexed citations
11.
Leipus, Remigijus & Jonas Šiaulys. (2020). On a closure property of convolution equivalent class of distributions. Journal of Mathematical Analysis and Applications. 490(1). 124226–124226. 4 indexed citations
12.
Šiaulys, Jonas, et al.. (2018). The Gerber–Shiu Discounted Penalty Function for the Bi-Seasonal Discrete Time Risk Model. Informatica. 29(4). 733–756. 3 indexed citations
13.
Leipus, Remigijus, et al.. (2017). CLOSURE PROPERTY AND TAIL PROBABILITY ASYMPTOTICS FOR RANDOMLY WEIGHTED SUMS OF DEPENDENT RANDOM VARIABLES WITH HEAVY TAILS. Journal of the Korean Mathematical Society. 54(6). 1879–1903. 2 indexed citations
14.
Šiaulys, Jonas, et al.. (2016). The finite-time ruin probability for an inhomogeneous renewal risk model. Journal of Industrial and Management Optimization. 13(1). 207–222. 2 indexed citations
15.
Šiaulys, Jonas, et al.. (2015). Ruin Probabilities of a Discrete-time Multi-risk Model. Information Technology And Control. 44(4). 367–379. 2 indexed citations
16.
Yang, Yang, Remigijus Leipus, & Jonas Šiaulys. (2012). On the ruin probability in a dependent discrete time risk model with insurance and financial risks. Journal of Computational and Applied Mathematics. 236(13). 3286–3295. 13 indexed citations
17.
Yang, Yang, Remigijus Leipus, & Jonas Šiaulys. (2012). Precise large deviations for compound random sums in the presence of dependence structures. Computers & Mathematics with Applications. 64(6). 2074–2083. 9 indexed citations
18.
Yang, Yang, et al.. (2011). Uniform estimates for the finite-time ruin probability in the dependent renewal risk model. Journal of Mathematical Analysis and Applications. 383(1). 215–225. 16 indexed citations
19.
Šiaulys, Jonas, et al.. (2010). INVESTIGATION OF THE GERBER-SHIU DISCOUNTED PENALTY FUNCTION ON FINITE TIME HORIZON. Information Technology And Control. 39(1). 1 indexed citations
20.
Šiaulys, Jonas, et al.. (2006). Second order asymptotic behaviour of subordinated sequences with longtailed subordinator. Journal of Mathematical Analysis and Applications. 332(1). 22–31. 2 indexed citations

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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