IEEE Transactions on Automatic Control, Vol.46, No.1, 43-50, 2001
Weighted estimation and tracking for branching processes with immigration
For branching processes with immigration, we propose a new approach which allows us to consistently estimate the means m, lambda, and the variances sigma (2), b(2) of the offspring and immigration distributions, respectively. Generally, statistical results for branching processes are established under the well-known trichotomy m < 1, m = 1, and m > 1. For example, no parameters of the immigration distribution can be consistently estimated if m > 1. The purpose of this paper is to obtain, through the introduction of a suitable adaptive control, strongly consistent estimators for all the parameters m, lambda, sigma (2), and b(2) without any restriction on the range of m, Central limit theorems and laws of iterated logarithm are also provided.
Keywords:adaptive control;branching processes;central limit theorem;law of iterated logarithm;least-squares estimation