References
2006; Wiley; Linguagem: Inglês
10.1002/9781118165409.refs
ISSN1940-6347
AutoresForrest W. Young, Pedro Valero‐Mora, Michael Friendly,
Tópico(s)Statistical Methods and Applications
ResumoFree Access References Forrest W. Young, University of North Carolina at Chapel Hill, NC, USASearch for more papers by this authorPedro M. Valero-Mora, Universitat de Valencia, Valencia, SpainSearch for more papers by this authorMichael Friendly, York University, Toronto, CanadaSearch for more papers by this author Book Author(s):Forrest W. Young, University of North Carolina at Chapel Hill, NC, USASearch for more papers by this authorPedro M. Valero-Mora, Universitat de Valencia, Valencia, SpainSearch for more papers by this authorMichael Friendly, York University, Toronto, CanadaSearch for more papers by this author First published: 21 July 2006 https://doi.org/10.1002/9781118165409.refsBook Series:Wiley Series in Probability and Statistics AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat References Agresti, A. (1990). Categorical Data Analysis. Wiley, New York. Google Scholar Alba, R. D. (1987). Interpreting the parameters of log-linear models. Sociological Methods and Research, 16(1): 45– 77. CrossrefWeb of Science®Google Scholar Allison, T. and Cicchetti, D. V. (1976). Sleep in mammals: ecological and constitutional correlates. Science, 194(12): 732– 734. CrossrefCASPubMedWeb of Science®Google Scholar Andersen, E. B. (1996). Introduction to the Statistical Analysis of Categorical Data. Springer-Verlag, New York. Google Scholar Asimov, D. (1985). The Grand Tour: a tool for viewing multidimensional data. SIAM Journal on Scientific and Statistical Computing, 6(1): 128– 143. CrossrefWeb of Science®Google Scholar Ato, M. and Lopez, J. J. (1996). Análisis estadísticos para datos categóricos. Síntesis, Madrid. Google Scholar Barnett, V. and Lewis, T. (1995). Outliers in Statistical Data. Wiley, New York. Google Scholar Becker, R. (1994). A brief history of S. Bell Laboratories. Google Scholar Becker, R. A. and Chambers, J. M. (1981). S: A Language and System for Data Analysis. AT&T Bell Laboratories, Murray Hill, NJ. Google Scholar Becker, R. A. and Cleveland, W. S. (1987). Brushing scatterplots. Technometrics, 29: 127– 142. CrossrefPubMedWeb of Science®Google Scholar Becker, R. A. and Cleveland, W. S. (1988). The use of brushing and rotation for data analysis. In W. S. Cleveland and M. E. McGill, editors, Dynamic Graphics for Statistics, pages 247– 276. Brooks/Cole, Pacific Grove, CA. Web of Science®Google Scholar Becker, R. A., Chambers, J. M., and Wilks, A. R. (1988a). The New S Language. Brooks/Cole, Pacific Grove, CA. Web of Science®Google Scholar Becker, R. A., Cleveland, W. S., and Wilks, A. R. (1988b). Dynamic graphics for data analysis. In W. S. Cleveland and M. E. McGill, editors, Dynamic Graphics for Statistics, pages 1– 50. Brooks/Cole, Pacific Grove, CA. Google Scholar Becker, R. A., Cleveland, W. S., and Shyu, M. J. (1996). The design and control of trellis display. Journal of Computational and Graphical Statistics, 5: 123– 155. CrossrefGoogle Scholar Bertin, J. (1967). Semiologie graphique: les diagrammes, les reseaux, les cartes. Gauthier-Villars, Paris. Google Scholar Bertin, J. (1983). Semiology of Graphics. University of Wisconsin Press, Madison, WI. (English translation by W. Berg). Google Scholar Betz, D. (1985). An XLISP tutorial. Byte, 10(3): 211– 236. Google Scholar Bickel, P. J., Hammel, J. W., and O'Connell, J. W. (1975). Sex bias in graduate admissions: data from Berkeley. Science, 187: 398– 403. CrossrefCASPubMedWeb of Science®Google Scholar Bishop, Y. M. M., Fienberg, S. E., and Holland, P. W. (1988). Discrete Multivariate Analysis: Theory and Practice. MIT Press, Cambridge, MA. Google Scholar Box, G. E. P. and Cox, D. R. (1964). An analysis of transformations. Journal of the Royal Statistical Society, Series B, 26: 296– 311. Google Scholar Brooks, F. P. J. (1975). The Mythical Man-Month: Essays on Software Engineering. Addison Wesley, Reading, MA. CrossrefGoogle Scholar Brooks, F. P. J. (1995). The Mythical Man-month: Essays on Software Engineering ( 20th anniversary edition). Addison-Wesley, Reading, MA. Google Scholar Buck, S. F. (1960). A method of estimation of missing values in multivariate data suitable for use with an electronic computer. Journal of the Royal Statistical Society, 22(2): 67– 81. Google Scholar Buja, A. and Asimov, D. (1986). Grand tour methods: An outline. Computing Science and Statistics, 17: 63– 67. Google Scholar Buja, A., Hurley, D., and McDonald, J. A. (1988). Elements of a viewing pipeline for data analysis. In W. S. Cleveland and M. E. McGill, editors, Dynamic Graphics for Statistics, pages 277– 308. Brooks/Cole, Pacific Grove, CA. Google Scholar Chambers, J. M., Cleveland, W. S., Kleiner, B., and Tukey, P. A. (1983). Graphical Methods for Data Analysis. Wadsworth International Group, Belmont, CA. Google Scholar Christensen, J., Marks, J., and Shieber, S. (1992). Labeling point features on maps and diagrams. Technical Report TR-25-92, Harvard University, Cambridge, MA. Google Scholar Christensen, J., Marks, J., and Shieber, S. (1995). An empirical study of algorithms for point-feature label placement. ACM Transactions on Graphics, 14(3): 203– 232. CrossrefWeb of Science®Google Scholar Christensen, R. (1990). Log-Linear Models. Springer-Verlag, New York. CrossrefGoogle Scholar Cleveland, W. S. (1994a). The Elements of Graphing Data, revised edition. Hobart Press, Summit, NJ. Google Scholar Cleveland, W. S. (1994b). Visualizing Data. Hobart Press, Summit, NJ. Google Scholar Cleveland, W. C. and McGill, M. E. (1988). Dynamic Graphics for Statistics. CRC Press, Boca Raton, FL. Google Scholar Cook, R. D. and Weisberg, S. (1994). An Introduction to Regression Graphics. Wiley, New York. Wiley Online LibraryGoogle Scholar Cook, R. D. and Weisberg, S. (1999). Applied Regression Including Computing and Graphics. Wiley, New York. Wiley Online LibraryGoogle Scholar Cruz-Neira, C., Sandin, D. J., DeFanti, T. A., Kenyon, R. V., and Hart, J. C. (1992). The CAVE: audiovisual experience automatic virtual environment. Communications of the ACM, 35: 67– 72. CrossrefWeb of Science®Google Scholar Cutting, J. E. (2002). Representing motion in a static image: constraints and parallels in art, science, and popular culture. Perception, 31: 1165– 1193. CrossrefPubMedWeb of Science®Google Scholar de Leeuw, J. (2004). Personal communication. Google Scholar de Leeuw, J. (2005). On abandoning Xlisp-Stat. Journal of Statistical Software, 13(7): 1– 5. Web of Science®Google Scholar Dempster, A. P., Laird, N. M., and Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, 39: 1– 37. Wiley Online LibraryGoogle Scholar Donoho, A. W., Donoho, D. L., and Gasko, M. (1988). MacSpin: dynamic graphics on a desktop computer. IEEE Computer Graphics and Applications, 8(4): 51– 58. CrossrefWeb of Science®Google Scholar Eddy, W. F., Howe, S. E., Teitel, B. F., and Young, F. W. (1991). The future of statistical software. In National Research Council Forum. National Academies Press, Washington, DC. Google Scholar Eick, S. G. (1994). Data visualization sliders. In ACM Symposium on User Interface Software and Technology, pages 119– 120, Monterey, CA. Google Scholar Fisherkeller, M. A., Friedman, J. H., and Tukey, J. W. (1975). Prim-9: a data display and analysis system. In Pacific Regional Conference of the Association for Computing Machinery, San Francisco, CA. Google Scholar Fowlkes, E. B. (1971). User's manual for an on-line interactive system for probability plotting on the ddp-224 computer. Technical memorandum, AT&T Bell Laboratories, Murray Hill, NJ. Google Scholar Friendly, M. (1992). User's guide for MOSAICS. Technical Report 206, Psychology Department, York University, 4700 Keele Street, Toronto, Canada. Google Scholar Friendly, M. (1994). Mosaic displays for multi-way contingency tables. Journal of the American Statistical Association, 89: 190– 200. CrossrefWeb of Science®Google Scholar Friendly, M. (1995). Conceptual and visual models for categorical data. American Statistician, 49: 153– 160. CrossrefWeb of Science®Google Scholar Friendly, M. (1999). Extending mosaic displays: marginal, partial, and conditional views of categorical data. Journal of Computational and Statistical Graphics, 8: 373– 395. CrossrefWeb of Science®Google Scholar Friendly, M. (2000a). Re-visions of Minard. Statistical Computing and Statistical Graphics Newsletter, 12(1): 13– 19. Google Scholar Friendly, M. (2000b). Visualizing Categorical Data. SAS Institute, Cary, NC. Web of Science®Google Scholar Friendly, M. (2004). Milestones in the history of data visualization: a case study in statistical historiography. In W. Gaul and C. Weihs, editors, Studies in Classification, Data Analysis, and Knowledge Organization. Springer-Verlag, New York. Google Scholar Friendly, M. and Denis, D. J. (2001). The roots and branches of statistical graphics. Journal de la Societe Francaise de Statistique, 141(4): 51– 60. Google Scholar Friendly, M. and Denis, D. J. (2004). Milestones in the history of thematic cartography, statistical graphics, and data visualization. www.math.yorku.ca/SCS/Gallery/milestone/. Google Scholar Friendly, M. and Kwan, E. (2003). Effect ordering for data displays. Computational Statistics and Data Analysis, 43(4): 509– 539. CrossrefWeb of Science®Google Scholar Fuchs, H., Poulton, J., Eyles, J., Greer, T., Goldfeather, J., Ellsworth, D., Molnar, S., Turk, G., Tebbs, B., and Israel, L. (1989). Pixel-planes 5: a heterogeneous multiprocessor graphics system using processor-enhanced memories. In SIG-GRAPH ′89: Proceedings of the 16th ACM Annual Conference on Computer graphics and Interactive Techniques, New York, pages 79– 88. Google Scholar Gabriel, K. R. (1971). The biplot graphical display of matrices with applications to principal component analysis. Biometrika, ( 58): 453– 467. CrossrefWeb of Science®Google Scholar Gane, C. and Sarson, T. (1979). Structured Systems Analysis: Tools and Techniques. Prentice-Hall, Englewood Cliffs, NJ. Google Scholar Gifi, A. (1990). Nonlinear Multivariate Analysis. Wiley, New York. Google Scholar Gower, J. C. and Hand, D. J. (1996). Biplots. Chapman & Hall. Google Scholar Graham, J., Hofer, S., and MacKinnon, D. (1996). Maximizing the usefulness of data obtained with planned missing value patterns: an application of maximum likelihood procedures. Multivariate Behavioral Research, 31(2): 197– 218. CrossrefCASPubMedWeb of Science®Google Scholar Greenacre, M. J. (1993). Correspondence Analysis in Practice. Academic Press, London. Google Scholar Guerry, A. M. (1833). Essai sur la statistique morale de la france. Crochard, Paris. English translation: Whitt, H. P. and Reinking, V. W. Edwin Mellen Press, Lewiston, NY, (2002). Google Scholar Guvenir, H. A., Demiroz, G., and liter, N. (1998). Learning differential diagnosis of erythemato-squamous diseases using voting feature intervals. Artificial Intelligence in Medicine, 13: 147– 165. CrossrefCASPubMedWeb of Science®Google Scholar Haberman, S. J. (1973). The analysis of residuals in cross-classification tables. Biometrics, 29: 205– 220. CrossrefWeb of Science®Google Scholar Hartigan, J. A. and Kleiner, B. (1981). Mosaics for contingency tables. In Eddy, E. F., editor, Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface, Springer-Verlag, New York. Google Scholar Hartigan, J. A. and Kleiner, B. (1984). A mosaic of television ratings. American Statistician, 38: 153– 160. Google Scholar Henderson, H. V. and Velleman, P. F. (1981). Building regression models interactively:data originally collected from consumer reports. Biometrics, 37: 391– 411. CrossrefWeb of Science®Google Scholar Hesterberg, T. (1999). A graphical representation of Little's test for MCAR. Technical Report 94. MathSoft, Seattle, WA. Google Scholar Hofman, H. (2003). Constructing and reading mosaic plots. Computational Statistics and Data Analysis, 43(4): 565– 580. CrossrefWeb of Science®Google Scholar Hutchins, E. L., Hollan, J. D., and Norman, D. A. (1986). Direct manipulation interfaces. In D.A. Norman and S. W. Draper, editors, User Centered System Design: New Perspectives on Human–Computer Interaction, pages 87– 124. Lawrence Erlbaum Associates, Hillsdale, NJ. Google Scholar Ihaka, R. and Gentleman, R. (1996). R: a language for data analysis and graphics. Journal of Computational and Graphical Statistics, 5(3): 299– 314. CrossrefGoogle Scholar Inselberg, A. (1985). The plane with parallel coordinates. The Visual Computer, 1: 69– 97. CrossrefWeb of Science®Google Scholar JMP (1989–2002). Version 5. SAS Institute. Cary, NC. Google Scholar Jollife, I. T. (2002). Principal Components Analysis. Springer-Verlag, New York. Google Scholar Kim, K. H. and Bentler, P. M. (2002). Tests of homogeneity of means and covariance matrixes for multivariate incomplete data. Psychometrika, 67(4): 609– 624. CrossrefWeb of Science®Google Scholar Little, R. J. A. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83(4): 1198– 1202. Google Scholar Little, R. J. A. and Rubin, D. B. (1987). Statistical Analysis with Missing Data. Wiley, New York. Google Scholar Little, R. J. A. and Rubin, D. B. (2002). Statistical Analysis with Missing Data-second edition. Wiley, New York. Wiley Online LibraryGoogle Scholar Marsaglia, G. (1968). Random numbers fall mainly in the plane. Proceedings of the National Academy of Sciences USA, 61: 25– 28. CrossrefCASPubMedWeb of Science®Google Scholar McCloud, S. (1994). Understanding Comics. HarperCollins, New York. Google Scholar McCullagh, P. and Nelder, J. A. (1989). Generalized Linear Models. Chapman & Hall, London. CrossrefCASGoogle Scholar McDonald, J. A. (1982). Interactive graphics for data analysis. Ph.d. dissertation, Stanford University, Stanford, CA. Google Scholar McDonald, J. A. (1988). Orion I: interactive graphics for data analysis. In W. S. Cleveland and M. E. McGill, editors, Dynamic Graphics for Statistics, pages 179– 200, Brooks/Cole, Pacific Grove, CA. Web of Science®Google Scholar McGill, R., Tukey, J. W., and Larsen, W. A. (1978). Variations of boxplots. American Statistician, 32: 12– 16. CrossrefWeb of Science®Google Scholar Miller, G. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psycological Review, 63: 81– 97. CrossrefCASPubMedWeb of Science®Google Scholar Minard, C. J. (1844). Tableaux figuratifs de la circulation de quelques chemins de fer, lith. (n.s.). ENPC, 5860/C351, 5299/C307. Google Scholar Molina, J. G., Ledesma, R., Valero-Mora, P. M., and Young, F. W. (2005). A video tour through ViSta 6.4. Journal of Statistical Software, 13(8): 1– 13. Web of Science®Google Scholar Mosteller, F., Fienberg, S. E., and Rourke, R. E. K. (1983). Beginning Statistics with Data Analysis. Addison-Wesley, Reading, M.A.Google Scholar Muller, K. E. (1981). Relationships between redundancy analysis, canonical correlation, and multivariate regression. Psychometrika, 46: 139– 142. CrossrefWeb of Science®Google Scholar Nagel, H. and Granum, E. (2004). Explorative and dynamic visualization of data in virtual reality. Computational Statistics, 19(1): 55– 73. CrossrefWeb of Science®Google Scholar Nelson, L., Cook, D., and Cruz-Neira, C. (1999). XGobi vs. the C2: results of an experiment comparing data visualization in a 3D inmmersive virtual reality environment with a 2D workstation display. Computational Statistics: Special Issue on Interactive Graphical Data Analysis, 14(1): 39– 51. Web of Science®Google Scholar NIST/SEMATECH (2004). e-handbook of statistical methods. www.itl.nist.gov/div898/handbook. Google Scholar Noma, E. (1987). Heuristic method for label placement in scatterplots. Psychometrika, 52(3): 463– 468. CrossrefWeb of Science®Google Scholar North, C. and Shneiderman, B. (1997). A taxonomy of multiple window coordinations. Technical Report 3854, Computer Science Department, University of Maryland, College Park, MD. Google Scholar North, C. and Shneiderman, B. (2000). Snap-Together Visualization: A User Interface for Coordinating Visualizations via Relational Schemata. Advanced Visual Interfaces: 128– 135. Google Scholar Playfair, W. (1786). Commercial and Political Atlas: Representing, by Copper-Plate Charts, the Progress of the Commerce, Revenues, Expenditure, and Debts of England, during the Whole of the Eighteenth Century. Corry, London (3rd edition, Stockdale, London, 1801); French edition, Tableaux d'arithmétique linéaire, du commerce, des finances, et de la dette nationale de l'Angleterre, Chez Barrois l'Aine, Paris, 1789. Google Scholar Playfair, W. (1801). Statistical Breviary; Shewing, on a Principle Entirely New, the Resources of Every State and Kingdom in Europe. Wallis, London. Google Scholar Pattison, T. and Phillips, M. (2001). View coordination architecture for information visualisation. In Australian symposium on Information visualisation, Sidney, Australia. Google Scholar Preece, J., Rogers, I., Sharp, H., Benyon, D., Holland, S., and Carey, T. (1994). Human–Computer Interaction. Addison-Wesley, Wokingham, Berks, England. Google Scholar Rindskopf, D. (1990). Non-standard log-linear models. Psychological Bulletin, 108(1): 150– 162. CrossrefWeb of Science®Google Scholar Rubin, D. (1987). Multiple Imputation for Nonresponse in Surveys. Wiley, New York. Wiley Online LibraryGoogle Scholar Savage, S. (2002). Decision making with insight. Duxbury Press, Belmont, CA. Google Scholar Schafer, J. L. (1997). Analysis of Incomplete Multivariate Data. Chapman & Hall, London. CrossrefWeb of Science®Google Scholar Schafer, J. L. (1999). Multiple imputation: a primer. Statistical Methods in Medical Research, 8(1): 3– 15. CrossrefCASPubMedWeb of Science®Google Scholar Scott, D. W. (1992). Multivariate Density Estimation. Wiley, New York. Wiley Online LibraryGoogle Scholar Siegel, J. M. (1995). Phylogeny and the function of REM sleep. Behavioural Brain Research, 69: 29– 34. CrossrefCASPubMedWeb of Science®Google Scholar Silverman, B. W. (1986). Density Estimation for Statistics and Data Analysis. Chapman & Hall, London. CrossrefWeb of Science®Google Scholar St. Amant, R. (1997). Navigation for data analysis systems. Lecture Notes in Computer Science, 1280: 101– 109. CrossrefWeb of Science®Google Scholar Stevens, W. P., Myers, G. J., and Constantine, L. L. (1974). Structured design. IBM Systems Journal, 13(2): 115– 139. CrossrefWeb of Science®Google Scholar Stine, R. and Fox, J. (1996). Statistical Computing Environments for Social Research. Sage, Thousand Oaks, CA. Google Scholar Sturges, H. A. (1926). The choice of a class interval. Journal of the American Statistical Association, 21: 65– 66. CrossrefWeb of Science®Google Scholar Stuetzle, W. (1987). Plot windows. Journal of the American Statistical Association, 82(398): 466– 475CrossrefWeb of Science®Google Scholar Swayne, D. F. and Buja, A. (1998). Missing data in interactive high-dimensional data visualization. Computational Statistics, 13(1): 15– 26. Web of Science®Google Scholar Swayne, D., Cook, D., and Buja, A. (1998). XGobi: interactive dynamic data visualization in the X window system. Journal of Computational and Graphical Statistics 7(1): 113– 130. CrossrefWeb of Science®Google Scholar Swayne, D., Lang, D., Buja, A., and Cook, D. (2003). GGobi: evolving from XGobi into an extensible framework for interactive data visualization. Computational Statistics and Data Analysis, 43(4): 423. CrossrefWeb of Science®Google Scholar Symanzik, J., Cook, D., Kohlmeyer, B., and Cruz-Neira, C. (1996). Dynamic statistical graphics in the cave virtual reality environment. In Dynamic Statistical Graphics Workshop, Sidney, Australia. Google Scholar Symanzik, J., Cook, D., Kohlmeyer, B. D., Lechner, U., and Cruz-Neira, C. (1997). Dynamic statistical graphics in the C2 virtual reality environment. Computing Science and Statistics, 29: 41– 47. Google Scholar Theus, M. (2003). Interactive data visualization using Mondrian. Journal of Statistical Software, 7(11): 1– 9. Google Scholar Thornes, B. and Collard, J. (1979). Who Divorces? Routledge & Kegan, Paul, London. Google Scholar Tierney, L. (1988). Xlisp-Stat: a statistical environment based on the Xlisp language. Technical Report 528, School of Statistics, University of Minnesota, Minneapolis, MN. Google Scholar Tierney, L. (1990). Lisp-Stat: An Object Oriented Environment for Statistical Computing and Dynamic Graphics. Wiley-Interscience, New York. Wiley Online LibraryGoogle Scholar Tierney, L. (2005). Some notes on the past and future of Lisp-Stat. Journal of Statistical Software, 13(9): 1– 15. Web of Science®Google Scholar Tufte, E. R. (1983). The Visual Display of Quantitative Information. Graphics Press, Cheshire, England. CASPubMedGoogle Scholar Tufte, E. R. (1997). Visual Explanations: Images and Quantities, Evidence and Narrative. Graphics Press, Cheshire, England. Google Scholar Tukey, J. W. (1962). The future of data analysis. Annals of Mathematical Statistics, 33: 1– 67. CrossrefWeb of Science®Google Scholar Tukey, J. W. (1965). The technical tools of statistics. American Statistician, 19: 23– 28. Web of Science®Google Scholar Tukey, J. W. (1977). Exploratory Data Analysis. Addison-Wesley, Reading, MA. Google Scholar Turlach, B. A. (1993). Bandwidth selection in kernel density estimation: a review. Discussion paper 9232 Institut of Statistique, Louvain-la-Neuve, Belgium. Google Scholar Udina, F. (1999). Implementing interactive computing in an object-oriented environment. Economics Working Papers 419. Department of Economics and Business, Universitat Pompeu Fabra, Barcelona, Spain. Google Scholar Unwin, A. R., Hawkins, G., Hofman, H., and Siegl, B. (1996). Interactive graphics for data sets with missing values: Manet. Journal of Computational and Graphical Statistics, 5(2): 113– 122. Google Scholar Valero-Mora, P. M. and Udina, F. (2005). The health of Lisp-Stat. Journal of Statistical Software, 13(10): 1– 5. CrossrefWeb of Science®Google Scholar Valero-Mora, P. M., Young, F. W., and Friendly, M. (2003). Visualizing categorical data in ViSta. Computational Statistics and Data Analysis, 43(4): 495– 508. CrossrefWeb of Science®Google Scholar Valero-Mora, P. M., Rodrigo, M. F., and Young, F. W. (2004). Visualizing parameters from log-linear models. Computational Statistics, 19(1): 113– 133. CrossrefWeb of Science®Google Scholar Velleman, P. F. (1997). DataDesk Version 6.0: Statistics Guide. Data Description, Ithaka, NY. Google Scholar Velleman, P. F. and Velleman, A. Y. (1985). Data Desk. Data Description, Ithaka, NY. Google Scholar Velleman, P. F. and Wilkinson, L. (1993). Nominal, ordinal, interval, and ratio typologies are misleading. American Statistician, 47: 65– 72. CrossrefWeb of Science®Google Scholar Vermunt, J. K. (1997). Log-Linear Models for Event Histories. Sage, Thousand Oaks, CA. Google Scholar Wainer, H. (1988). Dynamic Graphics for Statistics, Comment on “Dynamic Graphics for Data analysis” by Becker, Cleveland and Wilks, pages 60– 62. Brooks/Cole, Pacific Grove, CA. Google Scholar Wainer, H. and Velleman, P. F. (2001). Statistical graphics: mapping the pathways of science. Annual Review of Psychology, 52: 305– 335. CrossrefCASPubMedWeb of Science®Google Scholar Wand, M. P. (1996). Data-based choice of histogram bin width. Statistical Computing and Graphics, 51(1): 59– 64. Web of Science®Google Scholar Wegman, E. J. (1990). Hyperdimensional data analysis using parallel coordinates. Journal of the American Statistical Association, 85(411): 664– 675. CrossrefWeb of Science®Google Scholar Wegman, E. J. and Symanzik, J. (2002). Immersive projection technology for visual data mining. Journal of Computational and Graphical Statistics, 11(1): 163– 188. CrossrefWeb of Science®Google Scholar Wegman, E. J., Symanzik, J., Vandersluis, J., Luo, Q., Camelli, F., Dzubay, A., Fu, X., Khumbah, N.-A., Moustafa, R., Wall, R., and Zhu, Y. (1999). The Mini-CAVE: a voice-controlled IPT environment. In Bulling, H. J. and Riedel, O., editors, Proceedings of the 3rd International Immersive Projection Technology Workshop, pages 179– 190, Springer-Verlag, Berlin. Google Scholar Wilhelm, A. F. X. (1990). A data model for interactive Statistical packages. In Proceedings of the Section on Statistical Graphics, pages 61– 70, Baltimore, ASA. Google Scholar Weisberg, S. (2005). Lost opportunities: Why we need a variety of statistical languages. Journal of Statistical Software, 13(1): 1– 12. Web of Science®Google Scholar Wilkinson, L. (1999). The Grammar of Graphics. Springer, New York. CrossrefGoogle Scholar Young, F. W. (1994). ViSta: The visual statistics system. Research Memorandum 94–1 (revised 1996). L.L. Thurstone Psychometric Laboratory, Chapel Hill, NC. Google Scholar Young, F. W. (1989). Visualizing six-dimensional structure with dynamic statistical graphics. Chance, 2: 22– 30. CrossrefGoogle Scholar Young, F., Faldowski, R., and McFarlane, M. (1993). Multivariate statistical visualization. In C. R. Rao, editor, Handbook of Statistics, volume 9, Computational Statistics, pages 959– 998. North Holland, New York. Web of Science®Google Scholar Young, F. W. and Lubinsky, D. J. (1995). Guiding data analysts with visual statistics strategies. Journal of Computational and Graphical Statistics, 4(4): 229– 250. CrossrefWeb of Science®Google Scholar Young, F. W. and Rheingans, P. (1991). Visualizing structure in high-dimensional multivariate data. IBM Journal of Research and Development, 35(1–2): 97– 107. CrossrefWeb of Science®Google Scholar Young, F. W. and Sarle, W. S. (1982). Exploratory multivariate data analysis. SAS Institute, Cary, NC. Google Scholar Young, F. W. and Smith, J. B. (1991). Towards a structured data analysis environment: a cognition based design. In A. Buja and P. A. Tukey, editors, Computing and Graphics in Statistics, pages 255– 279. Springer-Verlag, New York. Google Scholar Young, F., Valero-Mora, P., Faldowski, R., and Bann, C. M. (2003). Gossip: The arquitecture of spreadplots. Journal of Computational and Graphical Statistics, 12(1): 80– 100. CrossrefWeb of Science®Google Scholar Visual Statistics: Seeing Data with Dynamic Interactive Graphics ReferencesRelatedInformation
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