34 citations · 126 across the 14 of their papers we have counts for
7 papers · 1 filter
A measure of evidence based on the likelihood-ratio statistics
Alexandre G. Patriota
In this paper, we show that the likelihood-ratio measure (a) is invariant with respect to dominating sigma-finite measures, (b) satisfies logical consequences which are not satisfi…
A statistical test to identify differences in clustering structures
André Fujita, Daniel Y. Takahashi, Alexandre G. Patriota +1
Statistical inference on functional magnetic resonance imaging (fMRI) data is an important task in brain imaging. One major hypothesis is that the presence or not of a psychiatric…
Vector Autoregressive Models With Measurement Errors for Testing Ganger Causality
Alexandre G. Patriota, Joao R. Sato, Betsabe G. Blas
This paper develops a method for estimating parameters of a vector autoregression (VAR) observed in white noise. The estimation method assumes the noise variance matrix is known an…
A note on Influence diagnostics in nonlinear mixed-effects elliptical models
Alexandre G. Patriota
This paper provides general matrix formulas for computing the score function, the (expected and observed) Fisher information and the matrices (required for the assessment of lo…
Influence diagnostics in Birnbaum-Saunders nonlinear regression models
Artur J. Lemonte
We consider the issue of assessing influence of observations in the class of Birnbaum-Saunders nonlinear regression models, which is useful in lifetime data analysis. Our results g…
Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model
Alexandre G. Patriota, Artur J. Lemonte, Heleno Bolfarine
This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysic…
Bias correction in a multivariate normal regression model with general parameterization
Alexandre G. Patriota, Artur J. Lemonte
This paper develops a bias correction scheme for a multivariate normal model under a general parameterization. In the model, the mean vector and the covariance matrix share the sam…