We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
A new estimator for the multicollinear Poisson regression model: simulation and application.
- Authors
Lukman, Adewale F.; Adewuyi, Emmanuel; Månsson, Kristofer; Kibria, B. M. Golam
- Abstract
The maximum likelihood estimator (MLE) suffers from the instability problem in the presence of multicollinearity for a Poisson regression model (PRM). In this study, we propose a new estimator with some biasing parameters to estimate the regression coefficients for the PRM when there is multicollinearity problem. Some simulation experiments are conducted to compare the estimators' performance by using the mean squared error (MSE) criterion. For illustration purposes, aircraft damage data has been analyzed. The simulation results and the real-life application evidenced that the proposed estimator performs better than the rest of the estimators.
- Subjects
MAXIMUM likelihood statistics; POISSON regression; MEAN square algorithms; DATA analysis; SIMULATION methods &; models
- Publication
Scientific Reports, 2021, Vol 11, Issue 1, p1
- ISSN
2045-2322
- Publication type
Article
- DOI
10.1038/s41598-021-82582-w