IBC 2004 in parallel with ASC 2004 Presentation: Starship Regression: A Regression Method with Flexibly-Shaped Errors

Robert A. R. King, Richard Gerlach and Darren Wraith.

Statistics, School of Mathematical and Physical Sciences, University of Newcastle, Newcastle, Australia.

Abstract

We present a parametric regression method that allows great flexibility in the shape of the error distribution by modelling the errors with the generalised lambda distribution (gld). Our approach allows accurate estimates of 100(1-p)% prediction intervals in the face of severe departures from symmetry and with a wide variety of tailweights. The gld is a distribution that allows a great variety of shapes within one distributional form.

Parameter estimation is via the starship method. Estimates of sampling variation are obtained via a parametric bootstrap method.

We demonstrate the implementation of the method in an R package and illustrate its use with real datasets.

This presentation is based on a paper currently in preparation, and on a University of Newcastle Technical Report.

The method will implemented in the R package, gld (available soon, email for more details)

publication and conference paper details


Publications information
Robert King's page
Statistics
Mathematical and Physical Sciences
University of Newcastle
Robert King-photo
icon
File "rking/publ/ibc2004.html" last updated 03:32:36 PM, Fri Nov 28, 2003
comments to: robert.king@newcastle.edu.au