Bootstrap of the offspring mean in the critical process with a non-stationary immigration

In applications of branching processes, usually it is hard to obtain samples of a large size. Therefore, a bootstrap procedure allowing inference based on a small sample size is very useful. Unfortunately, in the critical branching process with stationary immigration the standard parametric bootstrap is invalid. In this paper, we consider a process with non-stationary immigration, whose mean and variance vary regularly with nonnegative exponents alpha and beta, respectively. We prove that 1 + 2 alpha is the threshold for the validity of the bootstrap in this model. If beta < 1 + 2 alpha, the standard bootstrap is valid and if beta > 1 + 2 alpha it is invalid. In the case beta = 1 + 2 alpha, the validity of the bootstrap depends on the slowly varying parts of the immigration mean and variance. These results allow LIS to develop statistical inferences about the parameters of the process in its early stages. (C) 2009 Elsevier B.V. All rights reserved.