Title :
Hurdle strict arcsine model
Author :
Ngor, Phang Yook ; Fu, Loh Er
Author_Institution :
Fac. of Comput. & Math. Sci., Univ. Teknol. MARA, Bandaraya, Malaysia
Abstract :
The hurdle model is a finite mixture model where the zeros are generated by a particular distribution while the positive counts are generated by another (truncated) distribution. The discrete distributions commonly considered for hurdle models are the Poisson and negative binomial distributions. The hurdle models are also widely used for over- and under-dispersed count data. In this study, a new hurdle model, which is hurdle strict arcsine model is developed and fitted to two simulated data sets. Maximum likelihood estimation method is used in estimating the parameters.
Keywords :
Poisson distribution; binomial distribution; maximum likelihood estimation; Poisson distributions; arcsine model; discrete distributions; finite mixture model; hurdle model; maximum likelihood estimation method; negative binomial distributions; Computational modeling; Data models; Econometrics; Mathematical model; Maximum likelihood estimation; Medical services; count data; maximum likelihood estimation method; mixture model; truncated distribution;
Conference_Titel :
Humanities, Science and Engineering Research (SHUSER), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-1311-7
DOI :
10.1109/SHUSER.2012.6268820
