All Outputs (4)

Local Principal Curves (2005)
Journal Article
Einbeck, J., Tutz, G., & Evers, L. (2005). Local Principal Curves. Statistics and Computing, 15(4), 301-313. https://doi.org/10.1007/s11222-005-4073-8

Principal components are a well established tool in dimension reduction. The extension to principal curves allows for general smooth curves which pass through the middle of a multidimensional data cloud. In this paper local principal curves are intro... Read More about Local Principal Curves.

Model free endurance markers based on the second derivative of blood lactate curves (2005)
Conference Proceeding
Newell, J., Einbeck, J., Madden, N., & McMillan, K. (2005). Model free endurance markers based on the second derivative of blood lactate curves. In A. R. Francis, K. M. Matawie, A. Oshlack, & G. K. Smyth (Eds.), Statistical solutions to modern problems ; proceedings of the 20th International Workshop on Statistical Modelling. Sydney, Australia, July 10-15, 2005 (357-364)

Blood lactate assessment is used regularly by exercise physiologists as a predictor of endurance performance. Typically fingertip blood samples are collected at selected running speeds on a treadmill and a plot of lactate concentration against worklo... Read More about Model free endurance markers based on the second derivative of blood lactate curves.

Making the EM algorithm for NPML estimation less sensitive to tuning parameters (2005)
Conference Proceeding
Einbeck, J., & Hinde, J. (2005). Making the EM algorithm for NPML estimation less sensitive to tuning parameters. In C. Cairns, J. Condon, R. Donaghy, A. Marshall, & B. Shaw (Eds.), CASI 2005 : Conference on Applied Statistics in Ireland (52-53)

Exploring Multivariate Data Structures with Local Principal Curves (2005)
Conference Proceeding
Einbeck, J., Tutz, G., & Evers, L. (2005). Exploring Multivariate Data Structures with Local Principal Curves. In C. Weihs, & W. Gaul (Eds.), Proceedings of the 28th Annual Conference of the Gesellschaft für Klassifikation, 9-11 March 2004, University of Dortmund (256-263)

A new approach to find the underlying structure of a multidimensional data cloud is proposed, which is based on a localized version of principal components analysis. More specifically, we calculate a series of local centers of mass and move through t... Read More about Exploring Multivariate Data Structures with Local Principal Curves.