This paper considers the estimation of parameters for the Poisson regression model in the
presence of high, but imperfect multicollinearity. To mitigate this problem, we suggest using …

Abstract Recently, Liu (1993) estimator draws an important attention to estimate the
regression parameters for an ill-conditioned linear regression model when the vector of …

The maximum likelihood (ML) method is used to estimate the unknown Gamma regression
(GR) coefficients. In the presence of multicollinearity, the variance of the ML method …

The binary logistic regression is a widely used statistical method when the dependent
variable has two categories. In most of the situations of logistic regression, independent …

This article introduces some Liu parameters in the linear regression model based on the
work of Shukur, Månsson, and Sjölander. These methods of estimating the Liu parameter d …

It is known that multicollinearity affects the maximum likelihood estimator (MLE) negatively
when estimating the coefficients in Poisson regression. Namely, the variance of MLE inflates …

In this article, we propose generalized two-parameter (GTP) estimators and an algorithm for
the estimation of shrinkage parameters to combat multicollinearity in the multinomial logit …

In this paper, we propose a new biased estimator called Liu-type estimator in gamma
regression models in the presence of collinearity. We also consider some other estimators …

Recently, the Bell regression model (BRM) is proposed to model a count variable. The BRM
is generally preferred over the Poisson regression model to overcome the restriction that the …

When product quality follows the Gamma distribution and is related to one or more covariate
(s), then Gamma regression model (GRM) profiling will be used. The Gamma profiling is …