Outputs (3)

Multivariate regression smoothing through the 'fallling net' (2011)
Conference Proceeding
Taylor, J., & Einbeck, J. (2011). Multivariate regression smoothing through the 'fallling net'. In D. Conesa, A. Forte, A. Lopez-Quilez, & F. Munoz (Eds.), 26th International Workshop on Statistical Modelling, 5-11 July 2011, Valencia, Spain ; proceedings (597-602)

We consider multivariate regression smoothing through a conditional mean shift procedure. By computing local conditional means iteratively over a set or grid of target points, at each iteration a `net' is formed which gently drifts towards the data c... Read More about Multivariate regression smoothing through the 'fallling net'.

Using principal curves to analyse traffic patterns on freeways (2011)
Journal Article
Einbeck, J., & Dwyer, J. (2011). Using principal curves to analyse traffic patterns on freeways. Transportmetrica, 7(3), 229-246. https://doi.org/10.1080/18128600903500110

Scatterplots of traffic speed versus flow have caught considerable attention over the last decades due to their characteristic half-moon like shape. Modelling data of this type is difficult as both variables are actually not a function of each other... Read More about Using principal curves to analyse traffic patterns on freeways.

Bandwidth Selection for Mean-shift based Unsupervised Learning Techniques: a Unified Approach via Self-coverage (2011)
Journal Article
Einbeck, J. (2011). Bandwidth Selection for Mean-shift based Unsupervised Learning Techniques: a Unified Approach via Self-coverage. Journal of pattern recognition research, 6(2), 175-192. https://doi.org/10.13176/11.288

The mean shift is a simple but powerful tool emerging from the computer science literature which shifts a point to the local center of mass around this point. It has been used as a building block for several nonparametric unsupervised learning techni... Read More about Bandwidth Selection for Mean-shift based Unsupervised Learning Techniques: a Unified Approach via Self-coverage.