| An approach to model clustered survival data with dependent censoring S Schneider, FN Demarqui, EA Colosimo, VD Mayrink Biometrical Journal 62 (1), 157-174, 2020 | 26 | 2020 |
| Sparse latent factor models with interactions: Analysis of gene expression data VD Mayrink, JE Lucas The Annals of Applied Statistics, 799-822, 2013 | 26 | 2013 |
| Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies GDR Gil, MA Costa, ALM Lopes, VD Mayrink Energy Economics 64, 373-383, 2017 | 22 | 2017 |
| Testing and Estimating the Non‐Disjunction Fraction in Meiosis I using Reference Priors RH Loschi, JVD Monteiro, GHMA Rocha, VD Mayrink Biometrical Journal: Journal of Mathematical Methods in Biosciences 49 (6 …, 2007 | 12 | 2007 |
| On computational aspects of Bayesian spatial models: influence of the neighboring structure in the efficiency of MCMC algorithms VD Mayrink, D Gamerman Computational Statistics 24, 641-669, 2009 | 11 | 2009 |
| Yang and Prentice model with piecewise exponential baseline distribution for modeling lifetime data with crossing survival curves FN Demarqui, VD Mayrink | 10 | 2021 |
| An unified semiparametric approach to model lifetime data with crossing survival curves FN Demarqui, VD Mayrink, SK Ghosh arXiv preprint arXiv:1910.04475, 2019 | 10 | 2019 |
| Bayesian factor models for the detection of coherent patterns in gene expression data VD Mayrink, JE Lucas | 10 | 2015 |
| Generalized inverse-Gaussian frailty models with application to TARGET neuroblastoma data LSC Piancastelli, W Barreto-Souza, VD Mayrink Annals of the Institute of Statistical Mathematics 73, 979-1010, 2021 | 9 | 2021 |
| Prior specifications to handle the monotone likelihood problem in the Cox regression model FM Almeida, EA Colosimo, VD Mayrink Statistics and Its Interface 11 (4), 687-698, 2018 | 9 | 2018 |
| Semiparametric generalized exponential frailty model for clustered survival data W Barreto-Souza, VD Mayrink Annals of the Institute of Statistical Mathematics 71, 679-701, 2019 | 8 | 2019 |
| Firth adjusted score function for monotone likelihood in the mixture cure fraction model FM Almeida, EA Colosimo, VD Mayrink Lifetime Data Analysis 27, 131-155, 2021 | 7 | 2021 |
| Bayesian detection of clusters in efficiency score maps: An application to Brazilian energy regulation MA Costa, LB Mineti, VD Mayrink, ALM Lopes Applied Mathematical Modelling 68, 66-81, 2019 | 7 | 2019 |
| How to compute protein residue contacts more accurately? PM Martins, VD Mayrink, S de A. Silveira, CH da Silveira, LHF de Lima, ... Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 60-67, 2018 | 6 | 2018 |
| A Bayesian hidden Markov mixture model to detect overexpressed chromosome regions VD Mayrink, FB Gonçalves Journal of the Royal Statistical Society Series C: Applied Statistics 66 (2 …, 2017 | 5 | 2017 |
| Bessel regression and bbreg package to analyse bounded data W Barreto‐Souza, VD Mayrink, AB Simas Australian & New Zealand Journal of Statistics 63 (4), 685-706, 2021 | 4 | 2021 |
| Building a platform for data-driven pandemic prediction: from data modelling to visualisation-the CovidLP Project D Gamerman, MO Prates, T Paiva, VD Mayrink CRC Press, 2021 | 3 | 2021 |
| Clustering non-linear interactions in factor analysis EC Amorim, VD Mayrink METRON 78 (3), 329-352, 2020 | 3 | 2020 |
| pexm: a JAGS module for applications involving the piecewise exponential distribution VD Mayrink, JDN Duarte, FN Demarqui arXiv preprint arXiv:2004.12359, 2020 | 3 | 2020 |
| Partnering With Authors to Enhance Reproducibility at JASA J Wrobel, EC Hector, L Crawford, LDA McGowan, N da Silva, J Goldsmith, ... Journal of the American Statistical Association, 1-3, 2024 | 2 | 2024 |