Proposed methods in estimating the ridge regression parameter in Poisson regression model


Abstract


The Poisson regression model is considered as an important model among the
linear logarithm models. It is usually used to model the count dependent variable. However, as in linear regression model, the multicollinearity problem
may be present leading to negatively affect the model parameter estimation.
In this study, several methods are proposed to estimate the ridge parameter. Monte-Carlo simulation studies with different factors were conducted to
evaluate the performance of the used estimators. The results demonstrate
the better performance of the proposed estimator compared to other used
estimators in terms of mean squared error (MSE).



DOI Code: 10.1285/i20705948v11n2p506

Keywords: Multicollinearity; ridge estimator; Poisson regression model.

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