Publicações de Membros do PPG - 2019

1. Lachos, V. H., A. Matos, L., Castro, L. M., & Chen, M. H. (2019). Flexible longitudinal linear mixed models for multiple censored responses data. Statistics in medicine, 38(6), 1074-1102.

2. Chaves, N. L., Azevedo, C. L., Vilca-Labra, F., & Nobre, J. S. (2019). A new Birnbaum-Saunders type distribution based on the skew-normal model under a centered parameterization. Chilean Journal of Statistics (ChJS), 10(1).

3. Rodrigues‐Peres, R. M., de S Carvalho, B., Anurag, M., Lei, J. T., Conz, L., Gonçalves, R., ... & Sarian, L. O. (2019). Copy number alterations associated with clinical features in an underrepresented population with breast cancer. Molecular Genetics & Genomic Medicine, 7(7), e00750.

4. Gonsales, M. C., Montenegro, M. A., Preto, P., Guerreiro, M. M., Coan, A. C., Quast, M. P., ... & Lopes-Cendes, I. (2019). Multimodal analysis of SCN1A missense variants improves interpretation of clinically relevant variants in Dravet syndrome. Frontiers in neurology, 10, 289.

5. Secolin, R., Mas-Sandoval, A., Arauna, L. R., Torres, F. R., de Araujo, T. K., Santos, M. L., ... & Comas, D. (2019). Distribution of local ancestry and evidence of adaptation in admixed populations. Scientific reports, 9(1), 13900.

6. Maruyama, S. R., Carvalho, B., González-Porta, M., Rung, J., Brazma, A., Gustavo Gardinassi, L., ... & de Miranda-Santos, I. K. (2019). Blood transcriptome profile induced by an efficacious vaccine formulated with salivary antigens from cattle ticks. npj Vaccines, 4(1), 53.

7. Fernández, M., García, J. E., Gholizadeh, R., & González‐López, V. A. (2020). Sample selection procedure in daily trading volume processes. Mathematical Methods in the Applied Sciences, 43(13), 7537-7549.

8. Cunha, C., Fernández, M., García, J. E., González-López, V. A., & Romano, N. (2019). A copula-based consistency analysis of education indicators. 4open, 2, 19.

9. Cordeiro, M. T. A., García, J. E., González-López, V. A., & Londoño, S. L. M. (2019). Classification of autochthonous dengue virus type 1 strains circulating in Japan in 2014. 4open, 2, 20.

10. Cordeiro, M. T. A., García, J. E., González-López, V. A., & Londoño, S. L. M. (2019). Stochastic profile of Epstein-Barr virus in nasopharyngeal carcinoma settings. 4open, 2, 25.

11. Chaves, N. L., Azevedo, C. L., Vilca-Labra, F., & Nobre, J. S. (2019). A new Birnbaum-Saunders type distribution based on the skew-normal model under a centered parameterization. Chilean Journal of Statistics (ChJS), 10(1).

12. Zambom, A. Z., Collazos, J. A., & Dias, R. (2019). Functional data clustering via hypothesis testing k-means. Computational Statistics, 34, 527-549.

13. González-López, V. A., Piovesana, M. C., & Romano, N. (2019). Tail conditional probabilities to predict academic performance. 4open, 2, 18.

14. Kiihl, S. F., Martinez-Garrido, M. J., Domingo-Relloso, A., Bermudez, J., & Tellez-Plaza, M. (2019). MLML2R: an R package for maximum likelihood estimation of DNA methylation and hydroxymethylation proportions. Statistical applications in genetics and molecular biology, 18(1), 20180031.

15. Pinheiro, H. P., Maia, R. P., Lima Neto, E. A., & Rodrigues-Motta, M. (2019). Zero-one augmented beta and zero-inflated discrete models with heterogeneous dispersion for the analysis of student academic performance. Statistical Methods & Applications, 28(4), 749-767.

16. da Rocha Silva, F. B., Miguel, D. C., Machado, V. E., Oliveira, W. H. C., Goulart, T. M., Tosta, C. D., ... & Pinto, M. C. (2019). Influence of Leishmania (Viannia) braziliensis infection on the attractiveness of BALB/c mice to Nyssomyia neivai (Diptera: Psychodidae). Plos one, 14(4), e0214574.

17. Trucíos, C., Zevallos, M., Hotta, L. K., & Santos, A. A. (2019). Covariance prediction in large portfolio allocation. Econometrics, 7(2), 19.

18. Zevallos, M. (2019). A note on forecasting daily Peruvian stock market volatility risk using intraday returns. Economia, 42(84), 94-101.

19. Abbara, O., & Zevallos, M. (2019). A note on stochastic volatility model estimation. Brazilian Review of Finance, 17(4), 22-32.

20. Lebensztayn, E., & Utria, J. (2019). A new upper bound for the critical probability of the frog model on homogeneous trees. Journal of Statistical Physics, 176, 169-179.

21. Lebensztayn, E., & Estrada, M. A. (2019). Laws of large numbers for the frog model on the complete graph. Journal of Mathematical Physics, 60(12).

22. de Bernardini, D. F., Gallesco, C., & Popov, S. (2019). An improved decoupling inequality for random interlacements. Journal of Statistical Physics, 177(6), 1216-1239.

23. Cascone, M. H., & Hotta, L. K. (2019). Quasi-maximum likelihood estimation of GARCH models in the presence of missing values. Journal of Statistical Computation and Simulation, 89(2), 292-314.

24. Trucíos, C., Hotta, L. K., & Pereira, P. L. V. (2019). On the robustness of the principal volatility components. Journal of Empirical Finance, 52, 201-219.

25. Matos, L. A., Lachos, V. H., Lin, T. I., & Castro, L. M. (2019). Heavy-tailed longitudinal regression models for censored data: a robust parametric approach. Test, 28, 844-878.

26. Montoril, M. H., Pinheiro, A., & Vidakovic, B. (2019). Wavelet‐based estimators for mixture regression. Scandinavian Journal of Statistics, 46(1), 215-234.

27. de Andrade Lima Neto, E., Pinheiro, A., & Gomes de Oliveira Ferreira, A. (2021). On wavelet to select the parametric form of a regression model. Communications in Statistics-Simulation and Computation, 50(9), 2619-2642.

28. Fonseca, R. V., & Pinheiro, A. (2020). Wavelet estimation of the dimensionality of curve time series. Annals of the Institute of Statistical Mathematics, 72(5), 1175-1204.

29. Trucíos, C. (2019). Forecasting Bitcoin risk measures: A robust approach. International Journal of Forecasting, 35(3), 836-847.

30. Trucíos, C., Tiwari, A. K., & Alqahtani, F. (2020). Value-at-risk and expected shortfall in cryptocurrencies’ portfolio: A vine copula–based approach. Applied Economics, 52(24), 2580-2593.

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