Smoothing techniques for visualisation

Bowman, A.W. (2008) Smoothing techniques for visualisation. In: Chen, C.H., Hardle, W. and Unwin, A. (eds.) Handbook of Data Visualization. Series: Springer Handbooks of Computational Statistics (3). Springer: Berlin, pp. 493-538. ISBN 9783540330363 (doi:10.1007/978-3-540-33037-0_20)

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Publisher's URL: http://dx.doi.org/10.1007/978-3-540-33037-0_20

Abstract

Graphical displays are often constructed to place principal focus on the individual observations in a dataset, and this is particularly helpful in identifying both the typical positions of datapoints and unusual or influential cases. However, in many investigations, principal interest lies in identifying the nature of underlying trends and relationships between variables, and so it is often helpful to enhance graphical displays in ways which give deeper insight into these features.This can be very beneficial both for small datasets, where variation can obscure underlying patterns, and large datasets, where the volume of data is so large that effective representation inevitably involves suitable summaries.

Item Type:Book Sections
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Bowman, Professor Adrian
Authors: Bowman, A.W.
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Handbook of Data Visualization
Publisher:Springer
ISBN:9783540330363

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