Faculty Member, Statistics Department, Shahid Beheshti University of Tehran, Tehran, Iran
Abstract
In this paper, the Hurdle regression model is introduced for count responses with a large number of zeros. A maximum likelihood estimation method is used to estimate the model parameters. An application of the introduced model to beamforming data is presented. In this example, there are a large number of zero claims, which illustrates the applicability of the model with a zero-swollen count response. Various count regression models are introduced in this paper to model such count responses. Among these introduced models are the Poisson Hurdle regression model and the negative binomial Hurdle regression model.
Bahrami Samani, E. (2018). Hardle, Swollen Poisson, and Swollen Negative Binomial Regression Models for Analyzing Count Data with Many Zeros. Andishe_ye Amari, 23(1), 89-97.
MLA
Bahrami Samani, E. "Hardle, Swollen Poisson, and Swollen Negative Binomial Regression Models for Analyzing Count Data with Many Zeros", Andishe_ye Amari, 23, 1, 2018, 89-97.
HARVARD
Bahrami Samani E. (2018). 'Hardle, Swollen Poisson, and Swollen Negative Binomial Regression Models for Analyzing Count Data with Many Zeros', Andishe_ye Amari, 23(1), pp. 89-97.
CHICAGO
E. Bahrami Samani, "Hardle, Swollen Poisson, and Swollen Negative Binomial Regression Models for Analyzing Count Data with Many Zeros," Andishe_ye Amari, 23 1 (2018): 89-97,
VANCOUVER
Bahrami Samani E. Hardle, Swollen Poisson, and Swollen Negative Binomial Regression Models for Analyzing Count Data with Many Zeros. Andishe_ye Amari. 2018;23(1):89-97 (In Persian).
