Abstract
This chapter will cover the uses of graphs for making graphs. This overloading of terms is an unfortunate historical circumstance that conflated graph-of-a-function usage with graph-of-vertices-and-edges usage. Vertex-edge graphs have long been understood as fundamental to the development of algorithms. It has become increasingly evident that vertex-edge graphs are also fundamental to the development of statistical graphics and visualizations.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Altschul, S., Bundschuh, R., Olsen, R. and Hwa, T. (2001). The estimation of statistical parameteers for local alignment score distributions., Nucleic Acids Research 29:251–261.
Battista, G.D., Eades, P., Tamassia, R. and Tollis, I. (1994). Algorithms for drawing graphs: an annotated bibliography, Computational Geometry: Theory and Applications 4:235–282.
Battista, G.D., Eades, P., Tamassia, T. and Tollis, I. (1999). Graph Drawing: Algorithms for the Visualization of Graphs, Prentice-Hall,. Upper Saddle River, NJ.
Bederson, B., Shneiderman, B. and Wattenberg, M. (2002). Ordered and quantum treemaps: Making effective use of 2d space to display hierarchies, ACM Transactions on Graphics (TOG) 21(4):833–854.
Box, G. E.P. and Jenkins, G.M. (1976). Time Series Analysis: Forecasting and Control (rev. ed.), Holden-Day, Oakland, CA.
Breiman, L., Friedman, J., Olshen, R. and Stone, C. (1984). Classification and Regression Trees, Wadsworth, Belmont, CA.
Brin, S. and Page, L. (1998). The anatomy of a large-scale hypertextual Web search engine, Computer Networks and ISDN Systems 30(1–7):107–117.
Carr, D.B., Littlefield, R.J., Nicholson, W.L. and Littlefield, J.S. (1987). Scatterplot matrix techniques for large n, Journal of the American Statistical Association 82:424–436.
Dirschedl, P. (1991). Klassifikationsbaumgrundlagen und -neuerungen, in W. Flischer, M. Nagel and R. Ostermann (eds), Interaktive Datenalyse mit ISP, Essen, pp. 15–30.
Gandhi, A. (2002). Content-based image retrieval: plant species identification, PhD thesis, Oregon State University.
Hartigan, J.A. (1975). Printer graphics for clustering, Journal of Statistical Computation and Simulation 4:187–213.
Hopcroft, J.E. and Wong, J.K. (1974). Linear time algorithm for isomorphism of planar graphs, STOC: ACM Symposium on Theory of Computing (STOC).
Johnson, B. and Shneiderman, B. (1991). Treemaps: A space-filling approach to the visualization of hierarchical information structures, Proceedings of the IEEE Information Visualization ’91, pp. 275–282.
Klein, P., Sebastian, T. and Kimia, B. (2001). Shape matching using edit-distance: an implementation, Twelfth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), Washington, D.C., pp. 781–790.
Kleiner, B. and Hartigan, J. (1981). Representing points in many dimensions by trees and castles, Journal of the American Statistical Association 76:260–269.
Kobsa, A. (2004). User experiments with tree visualization systems, Proceedings of the IEEE Information Visualization 2004, pp. 9–16.
Kruja, E., Marks, J., Blair, A. and Waters, R. (2001). A short note on the history of graph drawing, Graph Drawing : 9th International Symposium, GD 2001, Lecture Notes in Computer Science, Vol. 2265, Heidelberg, pp. 272–278.
Lamping, J., Rao, R. and Pirolli, P. (1995). A focus+context technique based on hyperbolic geometry for visualizing large hierarchies, Human Factors in Computing Systems: CHI 95 Conference Proceedings, pp. 401–408.
Lausen, B., Sauerbrei, W. and Schumacher, M. (1994). Classification and regression trees (CART) used for the exploration of prognostic factors measured on different scales, in P. Dirschedl and R. Ostermann (eds), Computational Statistics, Heidelberg, pp. 483–496.
Marchette, D. (2004). Random Graphs for Statistical Pattern Recognition, John Wiley & Sons, New York.
Minnotte, M. and Scott, D. (1993). The mode tree: A tool for visualization of nonparametric density features, Journal of Computational and Graphical Statistics 2:51–68.
Phan, D., Yeh, R., Hanrahan, P. and Winograd, T. (2005). Flow map layout, Proceedings of the IEEE Information Visualization 2005, pp. 219–224.
Sakoe, H. and Chiba, S. (1978). Dynamic programming algorithm optimization for spoken word recognition, IEEE Transactions on Acoustics, Speech, and Signal Processing 26:43–49.
Shasha, D., Wang, J.T.-L. and Giugno, R. (2002). Algorithmics and applications of tree and graph searching, Symposium on Principles of Database Systems, pp. 39–52.
Skiena, S. (1998). The Algorithm Design Manual, Springer-Verlag, New York.
Torsello, A. (2004). Matching Hierarchical Structures for Shape Recognition, PhD thesis, University of York. citeseer.ist.psu.edu/torsello04matching.html.
Tukey, J.W. and Tukey, P. (1985). Computer graphics and exploratory data analysis: An introduction, National Computer Graphics Association, Fairfax, VA, United States.
Urbanek, S. (2003). Many faces of a tree, Computing Science and Statistics: Proceedings of the 35th Symposium on the Interface.
Vach, W. (1995). Classification trees, Computational Statistics 10:9–14.
White, R., Eisen, J., TL, T.K. and Fernald, R. (1998). Second gene for gonadotropin-releasing hormone in humans, Proceedings of the Natlional Academy of Sciences, Vol. 95, pp. 305–309.
Wilkinson, L. (1999). The Grammar of Graphics, Springer-Verlag, New York.
Wilkinson, L. (2005). The Grammar of Graphics (2nd edn.), Springer-Verlag, New York.
Wilkinson, L., Anand, A. and Grossman, R. (2005). Graph-theoretic scagnostics, Proceedings of the IEEE Information Visualization 2005, pp. 157–164.
Wills, G.J. (1999). NicheWorks – interactive visualization of very large graphs, Journal of Computational and Graphical Statistics 8(2):190–212.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Wilkinson, L. (2008). Graph-theoretic Graphics. In: Handbook of Data Visualization. Springer Handbooks Comp.Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-33037-0_6
Download citation
DOI: https://doi.org/10.1007/978-3-540-33037-0_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33036-3
Online ISBN: 978-3-540-33037-0
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)