Applied Mathematics & Information Sciences

Author Country (or Countries)

Saudi Arabia


The aim of this paper is to introduce a new estimator for the modified Jackknified Liu Type Negative Binomial. As in the presence of multicollinearity, the Maximum Likelihood Estimator (MLE) is unable to produce valid statistical inference. So, this paper is designed to solve the problem of multicollinearity. Several ridge regression estimators are used for this purpose. Moreover, Monte Carlo simulation and real life data set are applied on the proposed and existing estimators to evaluate the performance of proposed estimator in the case of MSE. The results reveal that our proposed estimator has best performance among all other estimators (i.e.ML,NBRR,LTNB,JNBR).

Digital Object Identifier (DOI)