A BAESIAN APPROACH TO MODEL THE CONDITIONAL DEMAND OF ELETRIC ENERGY OF RESIDENTIAL CONSUMES / UMA ABORDAGEM BAYESIANA PARA OS MODELOS DE DEMANDA CONDICIONAL PARA O CONSUMO RESIDENCIAL DE ENERGIA ELÉTRICA

AUTOR(ES)

ANA MARIA LIMA DE FARIAS

DATA DE PUBLICAÇÃO

1999

RESUMO

Conditional demand analysis (CDA) is an econometric method that, applied to studies of consumption of energy in the household sector, allows us to estimate the demand of energy for different appliances. In this thesis, the estimation of the CDA models is made in a Bayesian framework. The truncated normal distribution is used as a prior of the parameters, assuring their nonnegativity restrictions. Since the resulting posteriors are truncated distributions too, the Gibbs sampler is applied in the estimation of those densities. The results obtained are applied to a dataset obtained from LIGHT, one of the electricity utilities of Rio de Janeiro, in order to obtain some appliances load curves.

ASSUNTO(S)

conditional demand models via marko chain modelos de demanda condicional normal truncada via cadeias de marko simulacoes estocasticas stochastic simulation truncated normal

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