MODELO DINÂMICO BAYESIANO PARA A DENSIDADE NORMAL TRUNCADA / DYNAMIC BAYESIAN MODEL FOR A TRUNCATED NORMAL
AUTOR(ES)
MONICA BARROS
DATA DE PUBLICAÇÃO
1993
RESUMO
This thesis describes a Dynamic Bayesian Model for a Truncated Normal distribution. The classical and static solution to the problem of finding estimators for the parameters of the original Normal distribution was treated by A.C. Cohen in the 1950s and 1960s R.C. Souza (1978) described in his Doctoral thesis a Dynamic Bayesian Model for this distribution, in which Information Theory concepts were used. The present thesis extends the dynamic formulation of West, Harrison and Migon by considering a distribution which is not a member of a an Exponential Family. Moreover, we extend the results derived by Souza by dropping the assumptions of a steady state model. Some real and simulated series are analyzed and, in particular, we compare our results with those obtained by souza.
ASSUNTO(S)
bayesian model truncated normal normal truncada modelo bayesiano
ACESSO AO ARTIGO
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