Lluı́s Bermúdez

572 total citations
38 papers, 371 citations indexed

About

Lluı́s Bermúdez is a scholar working on Statistics and Probability, Economics and Econometrics and Artificial Intelligence. According to data from OpenAlex, Lluı́s Bermúdez has authored 38 papers receiving a total of 371 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Statistics and Probability, 12 papers in Economics and Econometrics and 10 papers in Artificial Intelligence. Recurrent topics in Lluı́s Bermúdez's work include Statistical Methods and Bayesian Inference (12 papers), Insurance and Financial Risk Management (12 papers) and Bayesian Methods and Mixture Models (9 papers). Lluı́s Bermúdez is often cited by papers focused on Statistical Methods and Bayesian Inference (12 papers), Insurance and Financial Risk Management (12 papers) and Bayesian Methods and Mixture Models (9 papers). Lluı́s Bermúdez collaborates with scholars based in Spain, Greece and Australia. Lluı́s Bermúdez's co-authors include Dimitris Karlis, Montserrat Guillén, Mercedes Ayuso, Joaquín Pérez, Miguel Santolino, Manuela Alcañiz, Ana María Pérez Marín, Michel Denuit, D.A. Anaya and Jan Dhaene and has published in prestigious journals such as SHILAP Revista de lepidopterología, Accident Analysis & Prevention and Computational Statistics & Data Analysis.

In The Last Decade

Lluı́s Bermúdez

33 papers receiving 354 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lluı́s Bermúdez Spain 13 136 133 123 103 70 38 371
Roel Verbelen Belgium 8 115 0.8× 91 0.7× 126 1.0× 99 1.0× 88 1.3× 14 309
Jean Pinquet France 11 97 0.7× 336 2.5× 164 1.3× 72 0.7× 129 1.8× 26 538
Miguel Santolino Spain 13 51 0.4× 130 1.0× 162 1.3× 39 0.4× 56 0.8× 49 440
Julien Trufin Belgium 11 94 0.7× 123 0.9× 171 1.4× 47 0.5× 139 2.0× 46 293
Stephen R. Cosslett United States 6 243 1.8× 304 2.3× 32 0.3× 55 0.5× 9 0.1× 9 583
Jörgen Hellström Sweden 11 77 0.6× 189 1.4× 47 0.4× 23 0.2× 13 0.2× 30 453
Dodi Devianto Indonesia 11 39 0.3× 55 0.4× 87 0.7× 30 0.3× 36 0.5× 114 406
Luiz Renato Lima United States 14 56 0.4× 356 2.7× 67 0.5× 14 0.1× 12 0.2× 39 544
Rodney W. Strachan Australia 16 122 0.9× 584 4.4× 90 0.7× 51 0.5× 24 0.3× 45 847

Countries citing papers authored by Lluı́s Bermúdez

Since Specialization
Citations

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

Fields of papers citing papers by Lluı́s Bermúdez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lluı́s Bermúdez

This figure shows the co-authorship network connecting the top 25 collaborators of Lluı́s Bermúdez. A scholar is included among the top collaborators of Lluı́s Bermúdez 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 Lluı́s Bermúdez. Lluı́s Bermúdez 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.
Bermúdez, Lluı́s & Dimitris Karlis. (2022). Copula-based bivariate finite mixture regression models with an application for insurance claim count data. Test. 31(4). 1082–1099. 3 indexed citations
2.
Guillén, Montserrat, et al.. (2021). Joint generalized quantile and conditional tail expectation regression for insurance risk analysis. Insurance Mathematics and Economics. 99. 1–8. 9 indexed citations
3.
Marín, Ana María Pérez, Montserrat Guillén, Manuela Alcañiz, & Lluı́s Bermúdez. (2019). Quantile Regression with Telematics Information to Assess the Risk of Driving above the Posted Speed Limit. Risks. 7(3). 80–80. 13 indexed citations
4.
Bermúdez, Lluı́s, et al.. (2018). Factores socio-académicos asociados a la tasa de abandono en el Grado de Estadística. SHILAP Revista de lepidopterología. 13–24.
5.
Bermúdez, Lluı́s, Dimitris Karlis, & Miguel Santolino. (2018). A discrete mixture regression for modeling the duration of non-hospitalization medical leave of motor accident victims. Accident Analysis & Prevention. 121. 157–165. 3 indexed citations
6.
Bermúdez, Lluı́s, Montserrat Guillén, & Dimitris Karlis. (2018). Allowing for time and cross dependence assumptions between claim counts in ratemaking models. Insurance Mathematics and Economics. 83. 161–169. 20 indexed citations
7.
Bermúdez, Lluı́s, Dimitris Karlis, & Miguel Santolino. (2017). A finite mixture of multiple discrete distributions for modelling heaped count data. Computational Statistics & Data Analysis. 112. 14–23. 5 indexed citations
8.
Bermúdez, Lluı́s, et al.. (2016). Análisis de la aparición de discapacidades en personas mayores de Cataluña. Revista de Métodos Cuantitativos para la Economía y la Empresa. 5.
9.
Ayuso, Mercedes, Lluı́s Bermúdez, & Miguel Santolino. (2014). The dynamics of one-sided incomplete information in motor disputes. International Review of Law and Economics. 41. 77–85. 6 indexed citations
10.
Bermúdez, Lluı́s & Dimitris Karlis. (2012). A finite mixture of bivariate Poisson regression models with an application to insurance ratemaking. Computational Statistics & Data Analysis. 56(12). 3988–3999. 33 indexed citations
11.
Bermúdez, Lluı́s, et al.. (2012). How to Use the Standard Model with Own Data?. SSRN Electronic Journal. 16 indexed citations
12.
Ferri, Antonio, Lluı́s Bermúdez, & Manuela Alcañiz. (2011). Sensibilidad a las correlaciones entre líneas de negocio del SCR del módulo de suscripción no vida basado en la fórmula estándar. 75–90.
13.
Bermúdez, Lluı́s, et al.. (2010). Valoración actuarial del perjuicio económico futuro derivado de los accidentes de tráfico. 141–160. 1 indexed citations
14.
Bermúdez, Lluı́s, et al.. (2010). Una metodología alternativa para el cálculo de los perjuicios económicos futuros ante la reforma del sistema de valoración del daño corporal. 53(141). 91–108. 1 indexed citations
15.
Bermúdez, Lluı́s & Dimitris Karlis. (2010). Modelling Dependence in a Ratemaking Procedure with Multivariate Poisson Regression Models. SSRN Electronic Journal. 15 indexed citations
16.
Bermúdez, Lluı́s, Montserrat Guillén, & Aïda Solé-Auró. (2009). Escenarios del impacto de la inmigración en la longevidad y la dependencia de los mayores en la población española. Revista Española de Geriatría y Gerontología. 44(1). 19–24. 1 indexed citations
17.
Bermúdez, Lluı́s, et al.. (2008). Análisis de la aparición de discapacidades en personas mayores de Cataluña // Analysis of disability onset of the elderly in Catalonia. Revista de Métodos Cuantitativos para la Economía y la Empresa. 5(1). 3–16. 1 indexed citations
18.
Bermúdez, Lluı́s, et al.. (2008). Tipologías sociodemográficas de individuos con dependencia en España y su supervivencia en estado de salud. Revista Española de Geriatría y Gerontología. 43(1). 19–31. 1 indexed citations
19.
Gómez–Déniz, Emilio, et al.. (2005). Computing Bonus–Malus Premiums under Partial Prior Information. British Actuarial Journal. 11(2). 361–374. 1 indexed citations
20.
Bermúdez, Lluı́s, Michel Denuit, & Jan Dhaene. (2001). EXPONENTIAL BONUS-MALUS SYSTEMS INTEGRATING A PRIORI RISK CLASSIFICATION. Insecta mundi. 9. 84–112. 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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