Heleno Bolfarine

4.2k total citations
210 papers, 2.8k citations indexed

About

Heleno Bolfarine is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Heleno Bolfarine has authored 210 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 193 papers in Statistics and Probability, 57 papers in Artificial Intelligence and 50 papers in Statistics, Probability and Uncertainty. Recurrent topics in Heleno Bolfarine's work include Statistical Distribution Estimation and Applications (119 papers), Statistical Methods and Bayesian Inference (103 papers) and Advanced Statistical Methods and Models (66 papers). Heleno Bolfarine is often cited by papers focused on Statistical Distribution Estimation and Applications (119 papers), Statistical Methods and Bayesian Inference (103 papers) and Advanced Statistical Methods and Models (66 papers). Heleno Bolfarine collaborates with scholars based in Brazil, Chile and Colombia. Heleno Bolfarine's co-authors include Héctor W. Gómez, Víctor H. Lachos, Reinaldo B. Arellano‐Valle, Gilberto A. Paula, Manuel Galea, Guillermo Martínez‐Flórez, Jorge L. Bazán, Edwin M. M. Ortega, Shelemyahu Zacks and Márcia D. Branco and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Technometrics.

In The Last Decade

Heleno Bolfarine

199 papers receiving 2.7k citations

Peers

Heleno Bolfarine

SPU

MSOR

FINAN

Reinaldo B. Arellano‐Valle Chile

Mohammad Ahsanullah United States

Arjun K. Gupta United States

Antonella Capitanio Italy

M. Masoom Ali United States

William R. Schucany United States

C. D. Lai New Zealand

William E. Strawderman United States

Edward J. Dudewicz United States

Sanat K. Sarkar United States

Reinaldo B. Arellano‐Valle Chile

Heleno Bolfarine

2.1k ×0.9

886 ×1.1

609 ×0.9

SPU

359 ×1.1

MSOR

549 ×1.9

FINAN

Citations per year, relative to Heleno Bolfarine Heleno Bolfarine (= 1×) peers Reinaldo B. Arellano‐Valle

Countries citing papers authored by Heleno Bolfarine

Since Specialization

Citations

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

Fields of papers citing papers by Heleno Bolfarine

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heleno Bolfarine

This figure shows the co-authorship network connecting the top 25 collaborators of Heleno Bolfarine. A scholar is included among the top collaborators of Heleno Bolfarine 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 Heleno Bolfarine. Heleno Bolfarine is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Bolfarine, Heleno, et al.. (2023). Regression modeling of censored data based on compound scale mixtures of normal distributions. Brazilian Journal of Probability and Statistics. 37(2). 1 indexed citations

Martínez‐Flórez, Guillermo, et al.. (2022). Modelling Asymmetric Data by Using the Log-Gamma-Normal Regression Model. Mathematics. 10(7). 1199–1199. 2 indexed citations

Bolfarine, Heleno, et al.. (2021). The Asymmetric Power-Student-t Model for Censored and Truncated Data. Anais da Academia Brasileira de Ciências. 93(4). e20190920–e20190920. 1 indexed citations

Bolfarine, Heleno, et al.. (2020). The Asymmetric Alpha-Power Skew-t Distribution. Symmetry. 12(1). 82–82. 2 indexed citations

Gallardo, Diego I. & Heleno Bolfarine. (2016). Two alternative estimation procedures for the negative binomial cure rate model with a latent activation scheme. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 1(1). 31–54. 1 indexed citations

Martínez‐Flórez, Guillermo, Heleno Bolfarine, & Héctor W. Gómez. (2015). Likelihood-based inference for the power regression model. QRU Quaderns de Recerca en Urbanisme. 39(2). 187–208. 3 indexed citations

Gómez, Héctor W., et al.. (2015). A new class of Skew-Normal-Cauchy Distribution. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 39(1). 35–50.

Bolfarine, Heleno, et al.. (2014). An extension of the slash-elliptical distribution. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 38(2). 215–230. 9 indexed citations

Bolfarine, Heleno, et al.. (2011). Statistical analysis of controlled calibration model with replicates. Journal of Statistical Computation and Simulation. 83(5). 941–961. 2 indexed citations

10.

Bazán, Jorge L., Heleno Bolfarine, & Márcia D. Branco. (2010). A Framework for Skew-Probit Links in Binary Regression. Communication in Statistics- Theory and Methods. 39(4). 678–697. 34 indexed citations

11.

Lachos, Víctor H., et al.. (2009). Multivariate measurement error models based on scale mixtures of the skew–normal distribution. Statistics. 44(6). 541–556. 31 indexed citations

12.

Lachos, Víctor H., et al.. (2008). Inference and local influence assessment in skew-normal null intercept measurement error model. Journal of Statistical Computation and Simulation. 78(3). 395–419. 8 indexed citations

13.

Gómez, Héctor W., et al.. (2008). A note on the likelihood and moments of the skew-normal distribution. Americanae (AECID Library). 32(1). 57–66. 9 indexed citations

14.

Castro, Mário de, et al.. (2008). Untitled. [Letter to the Editor]. Technometrics. 50(1). 86. 5 indexed citations

15.

Gómez, Héctor W., Francisco J. Torres, & Heleno Bolfarine. (2007). Large-Sample Inference for the Epsilon-Skew- t Distribution. Communication in Statistics- Theory and Methods. 36(1). 73–81. 35 indexed citations

16.

Ortega, Edwin M. M., Vicente G. Cancho, & Heleno Bolfarine. (2006). Influence diagnostics in exponentiated-Weibull regression models with censored data. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 30(2). 171–192. 26 indexed citations

17.

Aoki, Reiko, Heleno Bolfarine, & Júlio M. Singer. (2002). Asymptotic efficiency of method of moments estimators under null intercept measurement error regression models. Brazilian Journal of Probability and Statistics. 16. 157–167. 5 indexed citations

18.

Bolfarine, Heleno, et al.. (1997). Linear calibration in functional regression models. Communication in Statistics- Theory and Methods. 26(10). 2307–2328. 5 indexed citations

19.

Bolfarine, Heleno, Josemar Rodrigues, & S. Zacks. (1993). Some asymptotic results in finite populations. Statistics. 24(4). 359–370.

20.

Bolfarine, Heleno & Shelemyahu Zacks. (1992). Prediction Theory for Finite Populations. Springer series in statistics. 33 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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