In regression models in which a covariate is measured with error, it is common to use structures that correlate the observed covariate with the true non-observed covariate. Such structures are usually additive or ...

In this work a method for mixed-state model motion texture segmentation and parameter estimation is presented. We use the Expectation Maximization algorithm for mixture parameter estimation, introducing the Gibbs distribution ...

In this paper we present a novel approach for multispectral image contextual classification by combining iterative combinatorial optimization algorithms. The pixel-wise decision rule is defined using a Bayesian approach ...

The goal of this work is to analyze the returns to education in the hourly wages in Brazil for the period of 2011 to 2015, last five years of PNAD data. Even thought the relationship between years of education and wages ...

The Potts model is frequently used to describe the behavior of image classes, since it allows to incorporate contextual information linking neighboring pixels in a simple way. Its isotropic version has only one real parameter ...

This thesis proposes a novel family of multidimensional Cox processes with piece-wise constant intensity function and an exact Bayesian approach to perform statistical inference in this family. This family is based on the ...

This paper applies classical exponential-family statistical theory to develop a unifying framework for testing structural parameters in the simultaneous equations model under the assumption of normal errors with known ...