@article{(Open Science Index):https://publications.waset.org/pdf/10773,
	  title     = {Estimating Regression Effects in Com Poisson Generalized Linear Model},
	  author    = {Vandna Jowaheer and  Naushad A. Mamode Khan},
	  country	= {},
	  institution	= {},
	  abstract     = {Com Poisson distribution is capable of modeling the count responses irrespective of their mean variance relation and the parameters of this distribution when fitted to a simple cross sectional data can be efficiently estimated using maximum likelihood (ML) method. In the regression setup, however, ML estimation of the parameters of the Com Poisson based generalized linear model is computationally intensive. In this paper, we propose to use quasilikelihood (QL) approach to estimate the effect of the covariates on the Com Poisson counts and investigate the performance of this method with respect to the ML method. QL estimates are consistent and almost as efficient as ML estimates. The simulation studies show that the efficiency loss in the estimation of all the parameters using QL approach as compared to ML approach is quite negligible, whereas QL approach is lesser involving than ML approach.
},
	    journal   = {International Journal of Mathematical and Computational Sciences},
	  volume    = {3},
	  number    = {5},
	  year      = {2009},
	  pages     = {362 - 366},
	  ee        = {https://publications.waset.org/pdf/10773},
	  url   	= {https://publications.waset.org/vol/29},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 29, 2009},
	}