Predição de fator de simultaneidade através de modelos de regressão para proporções contínuas / Prediction of simultaneity factor using regression models for continuous proportions.
AUTOR(ES)
Luiz Fernando Molinari Zerbinatti
DATA DE PUBLICAÇÃO
2008
RESUMO
The simultaneity factor is fundamental in planning gas distribution networks. It is a multiplicator between 0 and 1 that adjusts the theoretical total consumption of a number of devices to realistic conditions. In 2005, the Instituto de Pesquisas Tecnológicas (IPT) and the Companhia de Gás de São Paulo (COMGÁS) performed a study in which the simultaneity factor of gas consumption in a set of residential buildings have been determined. A regression model was proposed to express the simultaneity factor in terms of the total power of installed equipment. The fitted model can be used to predict the simultaneity factor in new buildings. The model they proposed is a normal linear regression model in which the response variable is the logarithm of the simultaneity factor. In the present dissertation, our aim is to investigate other possible regression models suitable to the data obtained by IPT and CONGÁS. Emphasis is given to the beta regression model proposed by Ferrari and Cribari-Neto (Journal of Applied Statistics, 2004) which has a number of advantages over normal linear regression models. The beta regression model assumes that, given the covariates, the response variable has a beta distribution, which is adequate to model data observed in the unit interval. Therefore, no transformation in the response variable, the simultaneity factor, is needed. Additionally, we present a new approach for the prediction of the simultaneity factor, that is different from all the approaches shown in the literature, using the bootstrap technique.
ASSUNTO(S)
diagnóstico continuous proportions modelo de regressão beta fator de simultaneidade. prediction bootstrap simultaneity factor. beta regression model gas distribution network redes de distribuição de gás predição bootstrap proporções contínuas regression models diagnostic modelos de regressão
