MODEL REGRESI MIXED EFFECT ZERO-INFLATED POISSON; MIXED EFFECT ZERO-INFLATED POISSON REGRESSION MODEL

Ariani, Amalia Fajar, Danardono

2015 | Skripsi | FMIPA

Mixed Effect Zero-Inflated Poisson regression model is a regression model which used for modeling repeated measures or longitudinal data of count responses with excess zeros. Mixed ZIP model consists of Poisson regression and logistic regression with additional random effect in its Poisson regression model. Parameter estimation for mixed effect Zero-Inflated Poisson regression model is estimated by Maximum Likelihood Estimator (MLE) which uses Expectation Maximization (EM) algorithm for getting the MLE’s parameter. The best model selection is evaluated by comparing the MSE (Mean Square Error) score with other discrete regression models. Mixed effect Zero-Inflated Poisson model is applied in number of immature silverleaf whiteflies on poinsettia data. The result showed this model has the lowest MSE.

Kata Kunci : excess zero; mixed model; mixed effect Zero-Inflated Poisson.