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arXiv · 1511.06400

Minimum disparity estimation in controlled branching processes

Miguel Gonzalez·Carmen Minuesa·Ines del Puerto
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Abstract

Minimum disparity estimation in controlled branching processes is dealt with by assuming that the offspring law belongs to a general parametric family. Under some regularity conditions it is proved that the minimum disparity estimators proposed -based on the nonparametric maximum likelihood estimator of the offspring law when the entire family tree is observed- are consistent and asymptotic normally distributed. Moreover, it is discussed the robustness of the estimators proposed. Through a simulated example, focussing on the minimum Hellinger and negative exponential disparity estimators, it is shown that both are robust against outliers, being the negative exponential one also robust against inliers.

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Miguel Gonzalez, Carmen Minuesa, Ines del Puerto. 2015-11-19. Minimum disparity estimation in controlled branching processes. https://arxiv.org/abs/1511.06400

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