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What is Stein Estimator for COMPRM with Correlation about?

This study introduces a Stein estimator for the Conway-Maxwell Poisson regression model (COMPRM) to address issues of multicollinearity caused by correlated regressors. The proposed estimator is evaluated through theoretical comparisons and numerical simulations, demonstrating its superiority over the maximum likelihood estimator (MLE) in terms of mean square error. The findings suggest that the Stein estimator effectively manages both correlation and dispersion challenges in count data modeling.

Author

faizasajid05

Language

EN