Laws of iterated logarithm for MLE of generalized linear model randomly censored with incomplete information

In this paper, we define the generalized linear model (GLM) based on the observed data with incomplete information in the case of random censorship, and obtain a law of iterated logarithm and a Chung type law of iterated logarithm for the maximum likelihood estimator (MLE) βˆn in this model.