With a small sample size, n=30, you will have realizations of data where you will run into difficulties with the MLE of generalized Gamma distribution. This is mainly due to the `k' parameter. Increase the sample size (e.g., n=50 or 100) and this problem is less likely to happen (but can still happen). I would strongly suggest that when you are doing simulations, you should encapsulate the parameter estimation inside a `try' or `tryCatch' statement so that when there is an error, the simulation keeps going rather than crashing out. See the attached code. Best, Ravi Ravi Varadhan, Ph.D. (Biostatistics), Ph.D. (Environmental Engg) Associate Professor, Department of Oncology Division of Biostatistics & Bionformatics Sidney Kimmel Comprehensive Cancer Center Johns Hopkins University 550 N. Broadway, Suite 1111-E Baltimore, MD 21205 410-502-2619