Discussion of 'Beyond mean regression'

Green, PJ

Discussion of 'Beyond mean regression'

Green, PJ

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Publication Type:: Journal Article
Citation:: Statistical Modelling, 2013, 13 (4), pp. 305 - 315
Issue Date:: 2013-08-01

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Field	Value	Language
dc.contributor.author	Green, PJ https://orcid.org/0000-0002-4367-4756	en_US
dc.date.issued	2013-08-01	en_US
dc.identifier.citation	Statistical Modelling, 2013, 13 (4), pp. 305 - 315	en_US
dc.identifier.issn	1471-082X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/28125
dc.description.abstract	Methodology for regression beyond the mean has been a goal of researchers for many years. This discussion provides some additional context for the important ideas in the present paper, by recounting some of the historical background to the GAMLSS approach and pointing to the power and appeal of fully probabilistic regression analysis in the setting of Bayesian nonparametrics. © 2013 SAGE Publications.	en_US
dc.relation.ispartof	Statistical Modelling	en_US
dc.relation.isbasedon	10.1177/1471082X13494160	en_US
dc.subject.classification	Statistics & Probability	en_US
dc.title	Discussion of 'Beyond mean regression'	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	13	en_US
utslib.for	0104 Statistics	en_US
utslib.for	1403 Econometrics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	open_access
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	13	en_US

Abstract:

Methodology for regression beyond the mean has been a goal of researchers for many years. This discussion provides some additional context for the important ideas in the present paper, by recounting some of the historical background to the GAMLSS approach and pointing to the power and appeal of fully probabilistic regression analysis in the setting of Bayesian nonparametrics. © 2013 SAGE Publications.

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http://hdl.handle.net/10453/28125