Positive, right-skewed data with excess zeros are encountered in many real-life situations. Two possible techniques to analyze this type of data are: Two-part models and Tweedie models. The two-part models assume existence of a separate zero generating process, while the Tweedie models are based on distributions that allow mass at zero. The paper aims to present a simulation study to investigate the performance of Generalized Additive Models (GAM) under the distribution of Tweedie and two-part models for such data with excess zero by using MSE (Mean Square Error) and relative bias to compare the performance of both methods. We found that under different practical scenarios, the two-part model has a better performance than the Tweedie
