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.
Keywords
Collinearity; Jackknife estimator; K-L estimator, Monte Carlo simulation , Poisson regression model
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PDFDOI: http://dx.doi.org/10.21533/pen.v10i2.2935
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Copyright (c) 2022 Abed Ali Hamad, Zakariya Yahya Algamal
This work is licensed under a Creative Commons Attribution 4.0 International License.
ISSN: 2303-4521
Digital Object Identifier DOI: 10.21533/pen
This work is licensed under a Creative Commons Attribution 4.0 International License