EstimaÃÃo pontual e intervalar em um modelo de regressÃo Beta

AUTOR(ES)
DATA DE PUBLICAÇÃO

2004

RESUMO

In this thesis we consider the beta regression model recently proposed by Ferrari &CribariNeto (2003), which is tailored to situations where the response is restricted to the standard unit interval and has a regression structure involving regressors and unknown parameters. We derive the second order biases of the maximum likelihood estimators, and use them to define bia~-adju~ted estimators. As an alternative to the two analytically corrected estimators, we consider a bias correction mechanism via parametric bootstrap. The numerical evidence favors the bootstrap-biased estimator and the one obtained from the analytical corrective adjustment. Several different strategies for interval estimation are also considered. The thesis closes with an empirical application.

ASSUNTO(S)

direito publico ferrari &cribariâneto estimaÃÃo pontual modelo de regressÃo beta

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