Abstract
Pre-test estimation has been studied extensively for linear regression and simultaneous equation models. Recently attention has turned to pre-test estimation in non-linear models. This article studies pre-test maximum likelihood estimation in Poisson regression model. It presents its risk characteristics and compare them with those of restricted and unrestricted maximum likelihood estimators based on squared error loss function in a Monte Carlo experiment.
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