The minimum \(L_{2}\) distance estimator for Poisson mixture models

DOI10.1016/J.JSPI.2010.09.002zbMath1206.62050OpenAlexW1965115324MaRDI QIDQ619772

Shuyi Shen, Ian R. Harris

Publication date: 18 January 2011

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2010.09.002

zbMATH Keywords

robustnessinfluence functiondivergencemaximum likelihoodmixing proportion\(L_{2}\) distance

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Statistical aspects of information-theoretic topics (62B10)

Related Items (3)

Modelling of count data using nonparametric mixtures ⋮ A mixture model-based nonparametric approach to estimating a count distribution ⋮ Poisson-Gamma mixture processes and applications to premium calculation

Cites Work

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• An unbiased minimum distance estimator of the proportion parameter in a mixture of two normal distributions
• Minimum Hellinger distance estimation for Poisson mixtures.
• Robust estimation of \(k\)-component univariate normal mixtures
• Minimum Hellinger distance estimation of mixture proportions
• A Comparison of Minimum Distance and Maximum Likelihood Estimation of a Mixture Proportion
• Statistical analysis of finite mixture distributions
• The Influence Curve and Its Role in Robust Estimation
• Robust and efficient estimation by minimising a density power divergence

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