A Simulation Study of Some Biasing Parameters for the Ridge Type Estimation of Poisson Regression |
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Authors: | B. M. Golam Kibria Kristofer Månsson |
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Affiliation: | 1. Department of Mathematics and Statistics, Florida International University, Miami, Florida, USA;2. Department of Economics, Finance and Statistics, J?nk?ping University, J?nk?ping, Sweden |
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Abstract: | This article proposes several estimators for estimating the ridge parameter k based on Poisson ridge regression (RR) model. These estimators have been evaluated by means of Monte Carlo simulations. As performance criteria, we have calculated the mean squared error (MSE), the mean value, and the standard deviation of k. The first criterion is commonly used, while the other two have never been used when analyzing Poisson RR. However, these performance criteria are very informative because, if several estimators have an equal estimated MSE, then those with low average value and standard deviation of k should be preferred. Based on the simulated results, we may recommend some biasing parameters that may be useful for the practitioners in the field of health, social, and physical sciences. |
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Keywords: | Estimation MSE Multicollinearity Poisson Ridge regression Simulation |
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