Neste capıtulo caracterizamos estudos com estrutura longitudinal contrastando-os com
outros tipos, identificamos os conceitos que permeiam essa modalidade de investigaçao …

Local influence diagnostics based on estimating equations as the role of a gradient vector
derived from any fit function are developed for repeated measures regression analysis. Our …

Spatial linear models have been applied in numerous fields such as agriculture, geoscience
and environmental sciences, among many others. Spatial dependence structure modelling …

The current stock assessment model for American plaice (Hippoglossoides platessoides) on
the Grand Bank of Newfoundland (NAFO Divisions 3LNO) is a virtual population analysis …

Influence diagnostics have become important tools for statistical analysis since the seminal
work by Cook. In this article we present a curvature-based directional diagnostic, set up …

The retrospective problem involves systematic differences in sequential population analysis
(SPA) estimates of stock size or some other quantity in a reference year. The differences …

Estimating equations for analyzing correlated Birnbaum–Saunders (BS) data are derived in
this paper. A regression model is proposed for modeling the median of the life time until the …

This article aims to estimate parameters of spatial variability with Student's t-distribution by
the EM algorithm and present the study of local influence by means of two methods known …

In many situations we are interested in modeling data where there is no a clear relationship
between the response and the covariates. In the literature there are few related proposals …

In this paper we consider the capital asset pricing model under the multivariate normal
distribution for modeling asset returns. We develop and implement local influence diagnostic …