Minimum phi-divergence estimators for loglinear models with linear constraints and multinomial sampling

DOI10.1007/s00362-006-0370-3zbMath1183.62035OpenAlexW2036618960MaRDI QIDQ949420

Leandro Pardo, Nirian Martín

Publication date: 21 October 2008

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-006-0370-3

zbMATH Keywords

maximum likelihood estimatorloglinear modelsmultinomial samplingminimum phi-divergence estimator

Mathematics Subject Classification ID

Point estimation (62F10) Generalized linear models (logistic models) (62J12) Statistical aspects of information-theoretic topics (62B10)

Related Items (7)

The minimum \(S\)-divergence estimator under continuous models: the Basu-Lindsay approach ⋮ Poisson loglinear modeling with linear constraints on the expected cell frequencies ⋮ A family of the information criteria using the phi-divergence for categorical data ⋮ Analysis of \(\varPhi\)-divergence for loglinear models with constraints under product-multinomial sampling ⋮ New families of estimators and test statistics in log-linear models ⋮ New improved estimators for overdispersion in models with clustered multinomial data and unequal cluster sizes ⋮ Comparing two treatments in terms of the likelihood ratio order

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