Einbeck, J. and Isaac, B. and Evers, L. and Parente, A. (2012) 'Penalized regression on principal manifolds with application to combustion modelling.', in 27th International Workshop on Statistical Modelling, 16-20 July 2012, Prague, Czech Republic ; proceedings. Amsterdam: Statistical Modeling Society, pp. 117-122.
For multivariate regression problems featuring strong and non–linear dependency patterns between the involved predictors, it is attractive to reduce the dimension of the estimation problem by approximating the predictor space through a principal surface (or manifold). In this work, a new approach for non- parametric regression onto the fitted manifold is provided. The proposed penal- ized regression technique is applied onto data from a simulated combustion sys- tem, and is shown, in this application, to compare well with competing regression routines.
|Item Type:||Book chapter|
|Full text:||(AM) Accepted Manuscript|
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|Publisher Web site:||http://www.statmod.org/workshops_archive_proceedings_2012.htm|
|Date accepted:||No date available|
|Date deposited:||19 June 2013|
|Date of first online publication:||2012|
|Date first made open access:||No date available|
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