Michelli Barros

893 total citations
20 papers, 674 citations indexed

About

Michelli Barros is a scholar working on Statistics and Probability, Ocean Engineering and Statistics, Probability and Uncertainty. According to data from OpenAlex, Michelli Barros has authored 20 papers receiving a total of 674 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Statistics and Probability, 3 papers in Ocean Engineering and 3 papers in Statistics, Probability and Uncertainty. Recurrent topics in Michelli Barros's work include Statistical Distribution Estimation and Applications (16 papers), Advanced Statistical Methods and Models (7 papers) and Statistical Methods and Bayesian Inference (5 papers). Michelli Barros is often cited by papers focused on Statistical Distribution Estimation and Applications (16 papers), Advanced Statistical Methods and Models (7 papers) and Statistical Methods and Bayesian Inference (5 papers). Michelli Barros collaborates with scholars based in Brazil, Chile and United States. Michelli Barros's co-authors include Víctor Leiva, Gilberto A. Paula, Manoel Santos‐Neto, Manuel Galea, Francisco José A. Cysneiros, Antonio Sanhueza, Shuangzhe Liu, Raydonal Ospina and Viviana Giampaoli and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Sciences and Computational Statistics & Data Analysis.

In The Last Decade

Michelli Barros

17 papers receiving 662 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michelli Barros Brazil 12 563 201 127 77 74 20 674
Filidor Vilca Brazil 13 506 0.9× 187 0.9× 129 1.0× 71 0.9× 49 0.7× 40 567
Carolina Marchant Chile 16 531 0.9× 282 1.4× 125 1.0× 89 1.2× 95 1.3× 30 827
Malwane M. A. Ananda United States 11 442 0.8× 194 1.0× 69 0.5× 81 1.1× 137 1.9× 37 580
Zhenmin Chen United States 11 460 0.8× 314 1.6× 51 0.4× 33 0.4× 73 1.0× 34 617
Kahadawala Cooray United States 10 437 0.8× 231 1.1× 80 0.6× 110 1.4× 122 1.6× 19 562
Klaus L. P. Vasconcellos Brazil 12 410 0.7× 98 0.5× 79 0.6× 88 1.1× 58 0.8× 33 537
Eslam Hussam Saudi Arabia 13 426 0.8× 235 1.2× 50 0.4× 52 0.7× 77 1.0× 71 496
Sadegh Rezaei Iran 11 344 0.6× 261 1.3× 33 0.3× 37 0.5× 41 0.6× 39 452
Broderick O. Oluyede Botswana 16 805 1.4× 475 2.4× 74 0.6× 120 1.6× 94 1.3× 136 895
Vera Tomazella Brazil 12 335 0.6× 108 0.5× 62 0.5× 21 0.3× 53 0.7× 59 416

Countries citing papers authored by Michelli Barros

Since Specialization
Citations

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

Fields of papers citing papers by Michelli Barros

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michelli Barros

This figure shows the co-authorship network connecting the top 25 collaborators of Michelli Barros. A scholar is included among the top collaborators of Michelli Barros 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 Michelli Barros. Michelli Barros 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.
2.
Barros, Michelli, et al.. (2024). A Liquid Well Barrier Element for Temporary Plug and Abandonment Operations: A Breakthrough Approach. Processes. 12(10). 2190–2190. 1 indexed citations
3.
4.
Santos‐Neto, Manoel, Francisco José A. Cysneiros, Víctor Leiva, & Michelli Barros. (2022). Reparameterized Birnbaum–Saunders Distribution and its Moments, Estimation and Applications. SHILAP Revista de lepidopterología. 2 indexed citations
5.
Barros, Michelli, et al.. (2020). Bivariate Birnbaum-Saunders accelerated lifetime model: estimation and diagnostic analysis. Journal of Applied Statistics. 49(5). 1252–1276.
6.
Paula, Gilberto A., et al.. (2019). Analysis of correlated Birnbaum–Saunders data based on estimating equations. Test. 29(3). 661–681. 7 indexed citations
7.
Barros, Michelli, et al.. (2019). Failure rate of Birnbaum–Saunders distributions: Shape, change-point, estimation and robustness. Brazilian Journal of Probability and Statistics. 33(2). 16 indexed citations
8.
Barros, Michelli & Gilberto A. Paula. (2018). Discussion of “Birnbaum‐Saunders distributions: A review of models, analysis and applications”. Applied Stochastic Models in Business and Industry. 35(1). 96–99. 1 indexed citations
9.
Santos‐Neto, Manoel, Francisco José A. Cysneiros, Víctor Leiva, & Michelli Barros. (2016). Reparameterized Birnbaum-Saunders regression models with varying precision. Electronic Journal of Statistics. 10(2). 54 indexed citations
10.
Barros, Michelli, Manuel Galea, Víctor Leiva, & Manoel Santos‐Neto. (2016). Generalized Tobit models: diagnostics and application in econometrics. Journal of Applied Statistics. 45(1). 145–167. 22 indexed citations
11.
Leiva, Víctor, Manoel Santos‐Neto, Francisco José A. Cysneiros, & Michelli Barros. (2015). A methodology for stochastic inventory models based on a zero‐adjusted Birnbaum‐Saunders distribution. Applied Stochastic Models in Business and Industry. 32(1). 74–89. 29 indexed citations
12.
Leiva, Víctor, Manoel Santos‐Neto, Francisco José A. Cysneiros, & Michelli Barros. (2014). Birnbaum–Saunders statistical modelling: a new approach. Statistical Modelling. 14(1). 21–48. 66 indexed citations
13.
Barros, Michelli, et al.. (2014). Goodness-of-Fit Tests for the Birnbaum-Saunders Distribution With Censored Reliability Data. IEEE Transactions on Reliability. 63(2). 543–554. 29 indexed citations
14.
Paula, Gilberto A., Víctor Leiva, Michelli Barros, & Shuangzhe Liu. (2011). Robust statistical modeling using the Birnbaum‐Saunders‐tdistribution applied to insurance. Applied Stochastic Models in Business and Industry. 28(1). 16–34. 88 indexed citations
15.
Barros, Michelli, et al.. (2010). Influence diagnostics in the tobit censored response model. Statistical Methods & Applications. 19(3). 379–397. 38 indexed citations
16.
Barros, Michelli, Gilberto A. Paula, & Víctor Leiva. (2008). A new class of survival regression models with heavy-tailed errors: robustness and diagnostics. Lifetime Data Analysis. 14(3). 316–332. 75 indexed citations
17.
Barros, Michelli, Gilberto A. Paula, & Víctor Leiva. (2008). An R implementation for generalized Birnbaum–Saunders distributions. Computational Statistics & Data Analysis. 53(4). 1511–1528. 47 indexed citations
18.
Barros, Michelli, et al.. (2007). Hypothesis testing in the unrestricted and restricted parametric spaces of structural models. Computational Statistics & Data Analysis. 52(2). 1196–1207. 1 indexed citations
19.
Leiva, Víctor, Michelli Barros, Gilberto A. Paula, & Antonio Sanhueza. (2007). Generalized Birnbaum‐Saunders distributions applied to air pollutant concentration. Environmetrics. 19(3). 235–249. 92 indexed citations
20.
Leiva, Víctor, Michelli Barros, Gilberto A. Paula, & Manuel Galea. (2006). Influence diagnostics in log-Birnbaum–Saunders regression models with censored data. Computational Statistics & Data Analysis. 51(12). 5694–5707. 106 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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