For count responses, the situation of excess zeros (relative to what standard models allow) often occurs in biomedical and sociological applications. Modeling repeated measures of zero-inflated count data presents special challenges. This is because in addition to the problem of extra zeros, the correlation between measurements upon the same subject at different occasions needs to be taken into...

Zero inflation problem is very common in ecological studies as well as other areas. We propose the COnstrained Zero-Inflated Generalized Additive Model (COZIGAM) for analyzing zero-inflated data. Our approach assumes that the response follows some distribution from the zero-inflated 1-parameter exponential family, with the further assumption that the probability of zero inflation is some monoto...

With the popularity of big data analysis with insurance claim count data, diverse regression models for response variable have been developed. However, there is a multicollinearlity issue multivariate input variables to models. Recently, deep learning and neural network proposed, Keras Tensorflow-based model has also proposed. To apply non-normal we perform root mean square error accuracy compa...

In this paper, we propose a new generalization of the Poisson distribution by using concept weighted distribution; trigonometric weight with cosine function is used. We derive some distributional properties distribution, such as cumulative function, moment generating factorial moments, and index dispersion. Then, related model considered for modeling purposes, estimation parameters performed vi...