Jackknifing K-L estimator in Poisson regression model

Abstract

At the point when there is collinearity between the reaction variable and various illustrative factors, displaying the connection between the reaction variable and a few informative factors is troublesome. While surveying count information, the Poisson relapse model (PRM) is generally utilized in applied research. A shrinkage assessor is a consistently utilized answer for the multicollinearity issue. One of these shrinkage assessors is the Kibria and Lukman assessor (K-L). In this paper, a jackknifed variant of the K-L assessor in the Poisson relapse model is proposed, which consolidates the Jackknife interaction with the K-L assessor to diminish inclination. As far as outright inclination and mean squared blunder, our Monte Carlo recreation discoveries infer that the proposed assessor can give a critical improvement over other contending assessors.