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Vinicius D. Mayrink, Ph.D. - Publications

Affiliations: 
2011 Statistical Science Duke University, Durham, NC 
Area:
Bioinformatics, Statistics
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15 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2020 Mayrink VD, Gonçalves FB. Identifying atypically expressed chromosome regions using RNA-Seq data Statistical Methods and Applications. 29: 619-649. DOI: 10.1007/S10260-019-00496-4  0.501
2020 Mayrink VD, Panaro RV, Costa MA. Structural equation modeling with time dependence: an application comparing Brazilian energy distributors Asta Advances in Statistical Analysis. 1-31. DOI: 10.1007/S10182-020-00377-2  0.416
2019 Schneider S, Demarqui FN, Colosimo EA, Mayrink VD. An approach to model clustered survival data with dependent censoring. Biometrical Journal. Biometrische Zeitschrift. PMID 31729075 DOI: 10.1002/Bimj.201800391  0.397
2019 Duarte JDN, Mayrink VD. slfm: An R Package to Evaluate Coherent Patterns in Microarray Data via Factor Analysis Journal of Statistical Software. 90: 1-22. DOI: 10.18637/Jss.V090.I09  0.514
2019 Costa MA, Mineti LB, Mayrink VD, Lopes ALM. Bayesian detection of clusters in efficiency score maps: An application to Brazilian energy regulation Applied Mathematical Modelling. 68: 66-81. DOI: 10.1016/J.Apm.2018.11.009  0.336
2019 Barreto-Souza W, Mayrink VD. Semiparametric generalized exponential frailty model for clustered survival data Annals of the Institute of Statistical Mathematics. 71: 679-701. DOI: 10.1007/S10463-018-0658-9  0.422
2018 Almeida FM, Colosimo EA, Mayrink VD. Prior specifications to handle the monotone likelihood problem in the Cox regression model Statistics and Its Interface. 11: 687-698. DOI: 10.4310/Sii.2018.V11.N4.A12  0.353
2017 Mayrink VD, Gonçalves FB. A Bayesian hidden Markov mixture model to detect overexpressed chromosome regions Journal of the Royal Statistical Society Series C-Applied Statistics. 66: 387-412. DOI: 10.1111/Rssc.12178  0.367
2017 Gil GDR, Costa MA, Lopes ALM, Mayrink VD. Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies Energy Economics. 64: 373-383. DOI: 10.1016/J.Eneco.2017.04.009  0.366
2015 Mayrink VD, Lucas JE. Bayesian factor models for the detection of coherent patterns in gene expression data Brazilian Journal of Probability and Statistics. 29: 1-33. DOI: 10.1214/13-Bjps226  0.525
2015 Nunes Duarte JD, Mayrink VD. Factor analysis with mixture modeling to evaluate coherent patterns in microarray data Springer Proceedings in Mathematics and Statistics. 118: 185-195. DOI: 10.1007/978-3-319-12454-4_15  0.492
2013 Loschi RH, Mayrink VD. Reference Analysis in a Misclassification Model for the Meiosis I Nondisjunction Fraction in Trisomies International Scholarly Research Notices. 2013: 1-6. DOI: 10.5402/2013/905156  0.354
2013 Mayrink VD, Lucas JE. Sparse latent factor models with interactions: Analysis of gene expression data Annals of Applied Statistics. 7: 799-822. DOI: 10.1214/12-Aoas607  0.545
2009 Mayrink VD, Gamerman D. On computational aspects of Bayesian spatial models: Influence of the neighboring structure in the efficiency of MCMC algorithms Computational Statistics. 24: 641-669. DOI: 10.1007/S00180-009-0153-0  0.414
2007 Loschi RH, Monteiro JV, Rocha GH, Mayrink VD. Testing and estimating the non-disjunction fraction in Meiosis I using reference priors. Biometrical Journal. Biometrische Zeitschrift. 49: 824-39. PMID 17726717 DOI: 10.1002/Bimj.200710364  0.314
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