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In this paper, a new regression model for count response variable is proposed via re-parametrization of Poisson quasi-Lindley distribution. The maximum likelihood and method of moment estimations are considered to estimate the unknown parameters of re-parametrized Poisson quasi-Lindley distribution. The simulation study is conducted to evaluate the efficiency of estimation methods. The real data set...
We consider Poisson regression with the canonical link function. This regression model is widely used in regression analysis involving count data; one important application in electrical engineering is transmission tomography. In this paper, we establish the variable selection consistency and estimation consistency of the ℓ1-regularized maximum-likelihood estimator in this regression model, and characterize...
The standard statistical method for analyzing count data is the Poisson regression model, which is usually estimated using maximum likelihood (ML) method. The ML method is very sensitive to multicollinearity. Therefore, we present a new Poisson ridge regression estimator (PRR) as a remedy to the problem of instability of the traditional ML method. To investigate the performance of the PRR and the...
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