Abstract
Smoothing techniques are used to reduce the variability of point clouds. There is great interest not only among applied statisticians but also among applied workers in biostatistics, economics and engineering to model the data in a nonparametric fashion. The benefits of this more flexible modeling come at the cost of greater computation, especially in high dimensions. In this paper several possibilities of smoothing in high dimensions are described using additive models. The algorithms for solving the nonparametric smoothing problems are based on WARPing, i.e. Weighted Averaging using Rounded Points. Interactive graphical techniques are a conditio sine qua non for tuning and checking the structure of lower dimensional projections of the data and of smooths produced by the algorithms. Applications of the WARPing technique to a side impact study are shown by smoothing in Projection-Pursuit-type models using Average Derivative Estimation.
This research was supported by the Deutsche Forschungsgemeinschaft, Sonderforschungsbereich 303.
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Härdle, W. (1988). Efficient Nonparametric Smoothing in High Dimensions Using Interactive Graphical Techniques. In: Edwards, D., Raun, N.E. (eds) Compstat. Physica-Verlag HD. https://doi.org/10.1007/978-3-642-46900-8_2
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DOI: https://doi.org/10.1007/978-3-642-46900-8_2
Publisher Name: Physica-Verlag HD
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