TY - JOUR JF - JSS JO - JSS VL - 1 IS - 1 PY - 2007 Y1 - 2007/9/01 TI - Composite likelihood Inference in Parameter Driven Models TT - استنباط درستنمایی مرکب و ملاک انتخاب مدل در مدلهای مبتنی بر پارامتر N2 - In parameter driven models, the main problem is likelihood approximation and also parameter estimation. One approach to this problem is to apply simpler likelihoods such as composite likelihood. In this paper, we first introduce the parameter driven models and composite likelihood and then define a new model selection criterion based on composite likelihood. Finally, we demonstrate composite likelihood's capabilities in inferences and accurate model selection in parameter driven models throughout a simulation study. SP - 1 EP - 17 AU - Baghishani, Hossein AU - Tabatabaei, Mohammad Mahdi AD - Departement of Statistics, Ferdowsi University, Mashhad, Iran. KW - Count Data KW - Parameter Driven Models KW - MCEM Algorithm KW - Composite Likelihood KW - Kullback-Leibler Information KW - Window Subsampling. UR - http://jss.irstat.ir/article-1-1-en.html ER -