Publicações de Membros do PPG - 2020

1. Romeiro, R. G., Vilca, F., Balakrishnan, N., & Zeller, C. B. (2020). A robust multivariate Birnbaum–Saunders regression model. Statistics, 54(5), 1094-1123.

2. Chaves, N. L., Azevedo, C. L., Vilca-Labra, F., & Nobre, J. S. (2020). A log Birnbaum-Saunders regression model based on the skew-normal distribution under the centred parameterization. Statistics and Its Interface, 13(3), 335-346.

3. González-López, V. A., & de Moraes, R. R. (2020). A copula-based quantifying of the relationship between race inequality among neighbourhoods in São Paulo and age at death. 4open, 3, 11.

4. Fais, L. M. C. F., González-López, V. A., Rodrigues, D. S., & de Moraes, R. R. (2020). A copula based representation for tailings dam failures. 4open, 3, 12.

5. García, J. E., González-López, V. A., & Tasca, G. H. (2020). Partition Markov model for Covid-19 virus. 4open, 3, 13.

6. Pinheiro, H. P., Sen, P. K., Pinheiro, A., & Kiihl, S. F. (2020). A nonparametric approach to assess undergraduate performance. Statistica Neerlandica, 74(4), 538-558.

7. Lebensztayn, E., & Utria, J. (2018). Phase transition for the frog model on biregular trees. arXiv preprint arXiv:1811.05495.

8. Freguglia, V., Garcia, N. L., & Bicas, J. L. (2020). Hidden Markov random field models applied to color homogeneity evaluation in dyed textile images. Environmetrics, 31(4), e2613.

9. Sousa, A. R. D. S., Garcia, N. L., & Vidakovic, B. (2021). Bayesian wavelet shrinkage with beta priors. Computational Statistics, 36, 1341-1363.

10. Valeriano, K. A., Lachos, V. H., Prates, M. O., & Matos, L. A. (2021). Likelihood‐based inference for spatiotemporal data with censored and missing responses. Environmetrics, 32(3), e2663.

11. dos Santos Sousa, A. R. (2022). Bayesian wavelet shrinkage with logistic prior. Communications in Statistics-Simulation and Computation, 51(8), 4700-4714.

12. dos Santos Sousa, A. R. (2020). Taxa de Engajamento em Disciplinas Ministradas Na Modalidade a Distância. Revista Brasileira de Aprendizagem Aberta e a Distância, 19(1).

13. Garcia, N. L., Guttorp, P., & Ludwig, G. (2020). Interacting cluster point process model for epidermal nerve fibers. Spatial Statistics, 35, 100414.

14. Ludwig, G., Zhu, J., Reyes, P., Chen, C. S., & Conley, S. P. (2020). On spline-based approaches to spatial linear regression for geostatistical data. Environmental and ecological statistics, 27, 175-202.

15. Nogarotto, D. C., Azevedo, C. L. N., & Bazán, J. L. (2020). Bayesian modeling and prior sensitivity analysis for zero–one augmented beta regression models with an application to psychometric data. Brazilian Journal of Probability and Statistics, 34(2), 304-322.

16. Chaves, N. L., Azevedo, C. L., Vilca-Labra, F., & Nobre, J. S. (2020). A log Birnbaum-Saunders regression model based on the skew-normal distribution under the centred parameterization. Statistics and Its Interface, 13(3), 335-346.

17. Velho, R. M., Mendes, A. M. F., & Azevedo, C. L. N. (2020). Communicating science with YouTube videos: How nine factors relate to and affect video views. Frontiers in Communication, 5, 567606.

18. do Canto, A. M., Vieira, A. S., HB Matos, A., Carvalho, B. S., Henning, B., Norwood, B. A., ... & Lopes-Cendes, I. (2020). Laser microdissection-based microproteomics of the hippocampus of a rat epilepsy model reveals regional differences in protein abundances. Scientific Reports, 10(1), 4412.

19. Rocha, C. S., Secolin, R., Rodrigues, M. R., Carvalho, B. S., & Lopes-Cendes, I. (2020). The Brazilian Initiative on Precision Medicine (BIPMed): fostering genomic data-sharing of underrepresented populations. NPJ genomic medicine, 5(1), 42.

20. Hounkpe, B. W., Benatti, R. D. O., Carvalho, B. D. S., & De Paula, E. V. (2020). Identification of common and divergent gene expression signatures in patients with venous and arterial thrombosis using data from public repositories. PLoS One, 15(8), e0235501.

21. Lourenco, G. J., Oliveira, C., Carvalho, B. S., Torricelli, C., Silva, J. K., Gomez, G. V. B., ... & Lima, C. S. P. (2020). Inherited variations in human pigmentation-related genes modulate cutaneous melanoma risk and clinicopathological features in Brazilian population. Scientific Reports, 10(1), 12129.

22. Garcia-Rosa, S., Carvalho, B. S., Guest, P. C., Steiner, J., & Martins-de-Souza, D. (2020). Blood plasma proteomic modulation induced by olanzapine and risperidone in schizophrenia patients. Journal of proteomics, 224, 103813.

23. Corbi, S. C., de Vasconcellos, J. F., Bastos, A. S., Bussaneli, D. G., da Silva, B. R., Santos, R. A., ... & Scarel-Caminaga, R. M. (2020). Circulating lymphocytes and monocytes transcriptomic analysis of patients with type 2 diabetes mellitus, dyslipidemia and periodontitis. Scientific reports, 10(1), 8145.

24. Borges, M. G., Rocha, C. S., Carvalho, B. S., & Lopes-Cendes, I. (2020). Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosis. Genetics and Molecular Biology, 43(2), e20190270.

25. Cordeiro, M. T. A., García, J. E., González‐López, V. A., & Mercado Londoño, S. L. (2020). Partition Markov model for multiple processes. Mathematical Methods in the Applied Sciences, 43(13), 7677-7691.

26. García, J. E., & González-López, V. A. (2020). Random permutations, non-decreasing subsequences and statistical independence. Symmetry, 12(9), 1415.

27. García, J. E., González-López, V. A., da Silva, H. H., & Silva, T. S. (2020). Risk of fraud classification. 4open, 3, 9.

28. Saulo, H., Vila, R., Vilca, F., & Martínez, J. L. (2020). On asymmetric regression models with allowance for temporal dependence. Journal of Statistical Theory and Practice, 14, 1-23.

Responsável pelas informações nesta página: