期刊名称：International Journal of Statistics and Probability
印刷版ISSN：1927-7032
电子版ISSN：1927-7040
出版年度：2012
卷号：1
期号：2
页码：1
DOI：10.5539/ijsp.v1n2p1
出版社：Canadian Center of Science and Education
摘要：Count data sets often produce many zeros. It is sometimes potentially questionable to use a linear predictor to model the effect of a continuous covariate of interest in zero-inflated count data. To relax the restriction, Li (2011) proposed a semiparametric zero-inflated Poisson (ZIP) regression model by using fixed-knot cubic $basis$ splines or $B$-splines to model the covariate effect, and used the likelihood ratio test to assess the validity of the linear relationship between the natural logarithm of the Poisson mean and the covariate. A score test is conducted to assess whether the extra proportion of zeros in the semiparametric ZIP regression model is equal to zero.
