We use cookies to ensure that we give you the best experience on our website. By continuing to browse this repository, you give consent for essential cookies to be used. You can read more about our Privacy and Cookie Policy.

Durham Research Online
You are in:

Penalized regression on principal manifolds with application to combustion modelling.

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
Download PDF
Publisher Web site:
Date accepted:No date available
Date deposited:19 June 2013
Date of first online publication:2012
Date first made open access:No date available

Save or Share this output

Look up in GoogleScholar