11/2017 |
Fp2 - Maximal Curves with Many Automorphisms are Galois-Covered by the Hermitian Curve Daniele Bartoli, Maria Montanucci , Fernando Torres Let F be the finite field of order q2, q = ph with p prime. It is commonly rp-2017-11.pdf |

10/2017 |
Generalized Weierstrass Semigroups and their Poincaré Series J. J. Moyano-Fernández, W. Tenório , F. Torres We investigate the structure of the generalized Weierstraß semigroups at several points on a curve defined over a finite field. We present a description of these rp-2017-10.pdf |

9/2017 |
Zero-one Augmented Beta and Zero Inflated Discrete Models with Heterogeneous Dispersion: An Application to Students’ Academic Performance Hildete P. Pinheiro, Rafael P. Maia, Eufrásio A. Lima-Neto, Mariana Rodrigues-Motta The purpose of this work is to present suitable statistical methods to study the performance of undergraduate students based on the incidence/proportion of failed courses. Some approaches are considered: in one of them the incidence of failed courses is modeled using zero in ated discrete distributions with heteroscedasticity, considering rp-2017-09.pdf |

8/2017 |
Multidimensional Multiple Group IRT Models with Skew Normal Latent Trait Distributions Juan L. Padilla, Caio L. N. Azevedo, Victor H. Lachos Item response theory (IRT) models are one of the most important statistical tools for psychometric data analysis. Their applicability goes from educational rp-2017-08.pdf |

7/2017 |
Likelihood-based Inference for Zero-or-one Augmented Rectangular Beta Regression Models Ana R.S. Santos, Caio L. N. Azevedo, Jorge L. Bazan, Juvêncio S. Nobre A new zero-and/or-one augmented beta rectangular regression model is introduced in this work, which is based on a new parameterization of the rectangular beta distribution. Maximum likelihood estimation is performed by using a combination of the EM algorithm (for the continuous part) and Fisher scoring algorithm (for discrete part). Also, we develop techniques of model t assessment, by using the randomized quantile residuals and model selection, considering criteria, such as AIC and BIC.We conducted several simulation studies, considering some situations of practical interest, in order to evaluate the parameter recovery of the proposed model and estimation method, the impact of transforming the observed zeros and ones with the use of non-augmented models and the behavior of the model selection criteria. A psychometric real data set was analyzed to illustrate the performance of the new approach considering the model studied. rp-2017-07.pdf |

6/2017 |
Bayesian Inference for a Birnbaum-Saunders Regression Model Based on the Centered Skew Normal Distribution Nathalia L. Chaves, Caio L N Azevedo, Filidor Vilca-Labra and Juvêncio S. Nobre rp-2017-6.pdf |

5/2017 |
A Copula Based Modeling for Longitudinal IRT Data with Skewed Latent Distributions José Roberto Silva dos Santos, Caio Lucidius Naberezny Azevedo rp-2017-5.pdf |

4/2017 |
Bayesian General Cholesky Decomposition Based Modeling of Longitudinal Multiple-Group IRT Data with Skewed Latent Distributions and Growth Curves José Roberto Silva dos Santos , Caio Lucidius Naberezny Azevedo rp-2017-4.pdf |

3/2017 |
A General Cholesky Decomposition Based Modeling of Longitudinal IRT Data: Handling Skewed Latent Traits Distributions José Roberto Silva dos Santos, Caio Lucidius Naberezny Azevedo rp-2017-3.pdf |

2/2017 |
A General Cholesky Decomposition Based Modeling of Longitudinal IRT Data. José Roberto Silva dos Santos, Caio Lucidius Naberezny Azevedo rp-2017-2.pdf |