| On beta regression residuals PL Espinheira, SLP Ferrari, F Cribari-Neto Journal of Applied Statistics 35 (4), 407-419, 2008 | 227 | 2008 |
| Influence diagnostics in beta regression PL Espinheira, SLP Ferrari, F Cribari-Neto Computational Statistics & Data Analysis 52 (9), 4417-4431, 2008 | 130 | 2008 |
| FOCA: A methodology for ontology evaluation J Bandeira, II Bittencourt, P Espinheira, S Isotani arXiv preprint arXiv:1612.03353, 2016 | 65 | 2016 |
| Diagnostic tools in beta regression with varying dispersion SLP Ferrari, PL Espinheira, F Cribari‐Neto Statistica Neerlandica 65 (3), 337-351, 2011 | 55 | 2011 |
| Bootstrap prediction intervals in beta regressions PL Espinheira, SLP Ferrari, F Cribari-Neto Computational Statistics 29, 1263-1277, 2014 | 26 | 2014 |
| Model selection criteria on beta regression for machine learning PL Espinheira, LCM da Silva, AO Silva, R Ospina Machine Learning and Knowledge Extraction 1 (1), 26, 2019 | 21 | 2019 |
| Residual and influence analysis to a general class of simplex regression PL Espinheira, A de Oliveira Silva Test 29 (2), 523-552, 2020 | 17 | 2020 |
| Evaluating the impact of Mars and Venus Effect on the use of an Adaptive Learning Technology for Portuguese and Mathematics SJ De Santana, R Paiva, II Bittencourt, PE Ospina, RDA Silva, S Isotani 2016 IEEE 16th international conference on advanced learning technologies …, 2016 | 17 | 2016 |
| On nonlinear beta regression residuals PL Espinheira, EG Santos, F Cribari‐Neto Biometrical Journal 59 (3), 445-461, 2017 | 15 | 2017 |
| Prediction measures in beta regression models PL Espinheira, LCM da Silva, AO Silva arXiv preprint arXiv:1501.04830, 2015 | 13 | 2015 |
| What to do and what to avoid on the use of gamified intelligent tutor system for low-income students S Joaquim, II Bittencourt, R de Amorim Silva, PL Espinheira, M Reis Education and Information Technologies 27 (2), 2677-2694, 2022 | 12 | 2022 |
| Bias and variance residuals for machine learning nonlinear simplex regressions PL Espinheira, LCM Silva, F Cribari-Neto Expert Systems with Applications 185, 115656, 2021 | 10 | 2021 |
| Modified likelihood ratio tests for unit gamma regressions AC Guedes, F Cribari-Neto, PL Espinheira Journal of Applied Statistics 47 (9), 1562-1586, 2020 | 10 | 2020 |
| Beta regression model nonlinear in the parameters with additive measurement errors in variables D de Brito Trindade, PL Espinheira, KL Pinto Vasconcellos, ... Plos one 16 (7), e0254103, 2021 | 4 | 2021 |
| Bootstrap-based inferential improvements to the simplex nonlinear regression model AO Silva, JWA Silva, PL Espinheira Plos one 17 (8), e0272512, 2022 | 3 | 2022 |
| Bartlett-corrected tests for varying precision beta regressions with application to environmental biometrics AC Guedes, F Cribari-Neto, PL Espinheira Plos one 16 (6), e0253349, 2021 | 2 | 2021 |
| Nonlinear Simplex Regression Models P Espinheira, AO Silva arXiv preprint arXiv:1805.10843, 2018 | 1 | 2018 |
| Erratum to: Bootstrap prediction intervals in beta regressions PL Espinheira, SLP Ferrari, F Cribari-Neto Computational Statistics 32, 1777-1777, 2017 | 1 | 2017 |
| Estatística em Informática na Educação PE Ospina, R Paiva, D Dermeval, II Bittencourt Jornada de Atualização em Informática na Educação 4 (1), 95-135, 2015 | 1 | 2015 |
| Unit gamma regression models for correlated bounded data JVB de Freitas, JS Nobre, PL Espinheira, LC Rêgo Brazilian Journal of Probability and Statistics 37 (4), 693-719, 2023 | | 2023 |
