Conditional least squares estimators for the offspring mean in a subcritical branching process with immigration
Source of Publication
Communications in Statistics - Theory and Methods
Consider a Bienayme-Galton-Watson process with generation-dependent immigration, whose mean and variance vary regularly with non negative exponents and , respectively. We study the estimation problem of the offspring mean based on an observation of population sizes. We show that if <2, the conditional least squares estimator (CLSE) is strongly consistent. Conditions which are sufficient for the CLSE to be asymptotically normal will also be derived. The rate of convergence is faster than n 1/2, which is not the case in the process with stationary immigration. © 2012 Copyright Taylor and Francis Group, LLC.
Informa UK Limited
Medicine and Health Sciences
Consistency, Generation-dependent immigration, Offspring mean, Subcritical branching process, Weighted estimator
Rahimov, I., "Conditional least squares estimators for the offspring mean in a subcritical branching process with immigration" (2012). All Works. 1031.
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