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Generalisierte lineare Modelle mit zufälligen Effekten und variierenden KoeffizientenFunck-Hüsges, Claudia Beate. January 2001 (has links) (PDF)
Berlin, Techn. Univ., Diss., 2001. / Computerdatei im Fernzugriff.
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Generalisierte lineare Modelle mit zufälligen Effekten und variierenden KoeffizientenFunck-Hüsges, Claudia Beate. January 2001 (has links) (PDF)
Berlin, Techn. Univ., Diss., 2001. / Computerdatei im Fernzugriff.
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Überprüfung stochastischer Modelle mit Pseudo-ResiduenStadie, Andreas. January 2002 (has links) (PDF)
Göttingen, Univ., Diss., 2003. / Computerdatei im Fernzugriff.
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Überprüfung stochastischer Modelle mit Pseudo-ResiduenStadie, Andreas. January 2002 (has links) (PDF)
Göttingen, Univ., Diss., 2003. / Computerdatei im Fernzugriff.
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Überprüfung stochastischer Modelle mit Pseudo-ResiduenStadie, Andreas. January 2002 (has links) (PDF)
Göttingen, Universiẗat, Diss., 2003.
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Generalisierte lineare Modelle mit zufälligen Effekten und variierenden KoeffizientenFunck-Hüsges, Claudia Beate. Unknown Date (has links) (PDF)
Techn. Universiẗat, Diss., 2001--Berlin.
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Il ruolo svolto dalle fonti di finanziamento pubbliche nella dinamica di impresa : un'indagine valutativa empirica sulle piccole e medie imprese italiane secondo i Modelli Autoregressivi Generalizzati /Trovato, Giovanni. January 2001 (has links) (PDF)
Diss. Wirtsch.-wiss. St. Gallen, 2000 ; Nr. 2476. / Bibliogr.
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Flexible semi- and non-parametric modelling and prognosis for discrete outcomesBinder, Harald January 2006 (has links)
Zugl.: München, Univ., Diss., 2006
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Flexible Modellierung kategorialer ResponsevariablenScholz, Torsten. Unknown Date (has links) (PDF)
Universiẗat, Diss., 2004--München.
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DirichletReg: Dirichlet Regression for Compositional Data in RMaier, Marco J. 18 January 2014 (has links) (PDF)
Dirichlet regression models can be used to analyze a set of variables lying
in a bounded interval that sum up to a constant (e.g., proportions, rates,
compositions, etc.) exhibiting skewness and heteroscedasticity, without
having to transform the data.
There are two parametrization for the presented model, one using the common
Dirichlet distribution's alpha parameters, and a reparametrization of the
alpha's to set up a mean-and-dispersion-like model.
By applying appropriate link-functions, a GLM-like framework is set up that
allows for the analysis of such data in a straightforward and familiar way,
because interpretation is similar to multinomial logistic regression.
This paper gives a brief theoretical foundation and describes the
implementation as well as application (including worked examples) of
Dirichlet regression methods implemented in the package DirichletReg (Maier,
2013) in the R language (R Core Team, 2013). (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics
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