Unit Gamma/Gompertz Quantile Regression with Applications to Skewed Data

In this study, new unit quantile regression model, called the Unit Gamma/ Gompertz for bounded responses is developed by re-parameterizing Gamma/Gompertz distribution. To estimate parameters of maximum likelihood approach used to develop estimators parameters. Monte Carlo simulations are test consistency model. The application model illustrated using three real life datasets and results revealed that performs better than beta when response variable has skewed observations outliers.