Statistical Modelling 13 (4) (2013), 335–348
Discussion: A comparison of GAMLSS with quantile regression
RA Rigby
Statistics,
Operational Research and Mathematics (STORM) research centre,
London Metropolitan University,
UK
e-mail: r.rigby@londonmet.ac.uk
DM Stasinopoulos
Statistics,
Operational Research and Mathematics (STORM) research centre,
London Metropolitan University,
UK
V Voudouris
ESCP Europe Business School,
London,
UK
Abstract:
A discussion on the relative merits of quantile, expectile and GAMLSS regression models is given. We contrast the ‘complete distribution models’ provided by GAMLSS to the ‘distribution free models’ provided by quantile (and expectile) regression. We argue that in general, a flexibility parametric distribution assumption has several advantages allowing possible focusing on specific aspects of the data, model comparison and model diagnostics. A new method for concentrating only on the tail of the distributions is suggested combining quantile regression and GAMLSS.
Keywords:
GAMLSS; quantile and expectile regression; regression on the tail of the distribution
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