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Seminário
UFSCar/USP ? 30/09/2011 - 14h00
LOCAL: Sala de seminários
DEs-UFSCar TITLE: Bayesian modelling of
the mean and covariance matrix in normal nonlinear models PALESTRANTE: Prof. Dr. Edilberto
Cepeda Cuervo - Universidad Nacional de Colombia ABSTRACT: An important problem in statistics is the study of longitudinal data
taking into account the effect of other explanatory variables such as treatments
and time. In this paper, a new
Bayesian approach for analysing longitudinal data is proposed. This innovative
approach takes into account the possibility of having nonlinear regression
structures on the mean and linear regression structures on the
variance?covariance matrix of normal observations, and it is based on the
modelling strategy suggested by Pourahmadi [M. Pourahmadi, Joint mean-covariance
models with applications to longitudinal data: Unconstrained parameterizations,
Biometrika, 87 (1999), pp. 667?690.].We initially extend the classical
methodology to accommodate the fitting of nonlinear mean models then we propose
our Bayesian approach based on a generalization of the Metropolis?Hastings
algorithm of Cepeda (2001). Finally, we illustrate the proposed methodology by
analysing one example, the cattle data set, that is used to study cattle
growth. |