Paper Title
Estimation in the Type II Generalized Logistic Distribution Based on Progressively Type II Censored Data

Abstract
Generalized distributions has become widely used in applications recently. They are very flexible and superior in data analysis especially with skewed distributions that are important models and frequently used in many applications. More particular, the Generalized Logistic Distribution with its different types have lately gained a lot of attention. In this study, based on progressively type II censored data, we will estimate the unknown parameters of type II Generalized Logistic Distribution (Type II GLD). using different methods: Maximum likelihood estimators (MLE), and Bayesian inference. The estimators will be compared based on bias and Mean square error (MSE) using simulated and real data. Keywords - Point Estimation, Type II Generalized Logistic Distribution, Progressive Censoring.