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AN EXTENDED CLASS OF MARGINAL LINK FUNCTIONS FOR MODELLING CONTINGENCY TABLES BY EQUALITY AND INEQUALITY CONSTRAINTS
by
Bartolucci, Francesco
, Colombi, Roberto
, Forcina, Antonio
in
Inequality constraints
/ Linear transformations
/ Logical givens
/ Mathematical independent variables
/ Mathematical vectors
/ Matrices
/ Maximum likelihood estimators
/ Parameterization
/ Parametric models
/ Regression analysis
2007
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AN EXTENDED CLASS OF MARGINAL LINK FUNCTIONS FOR MODELLING CONTINGENCY TABLES BY EQUALITY AND INEQUALITY CONSTRAINTS
by
Bartolucci, Francesco
, Colombi, Roberto
, Forcina, Antonio
in
Inequality constraints
/ Linear transformations
/ Logical givens
/ Mathematical independent variables
/ Mathematical vectors
/ Matrices
/ Maximum likelihood estimators
/ Parameterization
/ Parametric models
/ Regression analysis
2007
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Do you wish to request the book?
AN EXTENDED CLASS OF MARGINAL LINK FUNCTIONS FOR MODELLING CONTINGENCY TABLES BY EQUALITY AND INEQUALITY CONSTRAINTS
by
Bartolucci, Francesco
, Colombi, Roberto
, Forcina, Antonio
in
Inequality constraints
/ Linear transformations
/ Logical givens
/ Mathematical independent variables
/ Mathematical vectors
/ Matrices
/ Maximum likelihood estimators
/ Parameterization
/ Parametric models
/ Regression analysis
2007
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AN EXTENDED CLASS OF MARGINAL LINK FUNCTIONS FOR MODELLING CONTINGENCY TABLES BY EQUALITY AND INEQUALITY CONSTRAINTS
Journal Article
AN EXTENDED CLASS OF MARGINAL LINK FUNCTIONS FOR MODELLING CONTINGENCY TABLES BY EQUALITY AND INEQUALITY CONSTRAINTS
2007
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Overview
We extend Bergsma and Rudas (2002)'s hierarchical complete marginal parameterization to allow for logits and higher order effects of global and continuation type which may be more suitable with ordinal data. We introduce a general definition of marginal interaction parameters and show that this parameterization constitutes a link function so that linear models defined by equality and inequality constraints may be fitted and tested by extending the methods of Colombi and Forcina (2001). Computation and asymptotic properties of maximum likelihood estimators are discussed, and the asymptotic distribution of the likelihood ratio test is derived.
Publisher
Institute of Statistical Science, Academia Sinica and International Chinese Statistical Association
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