Nonadditivity in loglinear models using \(\Phi\)-divergences and MLEs

DOI10.1016/j.jspi.2003.08.012zbMath1054.62078OpenAlexW2087499322MaRDI QIDQ1888842

María del Carmen Pardo, Leandro Pardo

Publication date: 29 November 2004

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.2003.08.012

zbMATH Keywords

Poisson samplingAsymptotic distributionsLoglinear modelsMultinomial samplingMandel's modelProduct-multinomial sampling

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Parametric hypothesis testing (62F03) Generalized linear models (logistic models) (62J12)

Related Items

Residual analysis and outliers in loglinear models based on phi-divergence statistics ⋮ Analysis of divergence in loglinear models when expected frequencies are subject to linear constraints ⋮ Minimum phi-divergence estimators for loglinear models with linear constraints and multinomial sampling ⋮ A method for detecting hidden additivity in two-factor unreplicated experiments ⋮ Power-Divergence Test Statistics for Testing Linear by Linear Association ⋮ Minimum \(\varphi\)-divergence estimator and \(\varphi\)-divergence statistics in generalized linear models with binary data

Cites Work

• Testing for nonadditivity in log-linear and logit models
• Model checking in loglinear models using \(\phi\)-divergences and MLEs
• One Degree of Freedom for Nonadditivity: Applications with Generalized Linear Models and Link Functions
• The Future of Data Analysis
• Non-Additivity in Two-Way Analysis of Variance
• Extensions of the General Linear Hypothesis Model
• An Analysis of a Two-Way Model with Interaction and No Replication
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