A generalized framework for modelling ordinal data

In several applied disciplines, as Economics, Marketing, Business, Sociology, Psychology, Political science, Environmental research and Medicine, it is common to collect data in the form of ordered categorical observations. In this paper, we introduce a class of models based on mixtures of discrete...

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Veröffentlicht in:	Statistical methods & applications Jg. 25; H. 2; S. 163 - 189
Hauptverfasser:	Iannario, Maria, Piccolo, Domenico
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2016 Springer Nature B.V
Schlagworte:	Applied mathematics Asymptotic methods Asymptotic properties Business Case studies Chemistry and Earth Sciences Computer Science Computer simulation Consistency Data analysis Economics Experiments Finance Generalized linear models Health Sciences Humanities Insurance Law Management Mathematics and Statistics Maximum likelihood method Medicine Physics Polls & surveys Preferences Probability Random variables Shelters Simulation Sociology Statistical analysis Statistical Theory and Methods Statistics Statistics for Business Statistics for Engineering Statistics for Life Sciences Statistics for Social Sciences models choices Rating survey Ordinal data
ISSN:	1618-2510, 1613-981X
Online-Zugang:	Volltext
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