Information Technology Reference
In-Depth Information
Gower, J.C. (2008) Asymmetry analysis: The place of models. In K. Shigemasu
et al.
(eds),
New
Trends in Psychometrics
, pp. 69 - 78. Tokyo: Universal Academy Press.
Gower, J.C. and Dijksterhuis, G.B. (2004)
Procrustes Problems
. Oxford: Oxford University Press.
Gower, J.C. and Hand, D.J. (1996)
Biplots
. London: Chapman & Hall.
Gower, J.C. and Harding, S. (1988) Nonlinear biplots.
Biometrika
,
75
, 445 - 455.
Gower, J.C. and Legendre, P. (1986) Metric and Euclidean properties of dissimilarity coefficients.
Journal of Classification
,
3
, 5 - 48.
Gower, J.C. and Ngouenet, R.F. (2005) Nonlinearity effects in multidimensional scaling.
Journal
of Multivariate Analysis
.
94
, 344 - 365.
Gower, J.C., Meulman, J.J. and Arnold, G.M. (1999) Non-metric linear biplots.
Journal of Clas-
sification
,
16
, 181 - 196.
Gower, J.C., Groenen, P.J.F. and Van de Velden, M. (2010) Area biplots.
Journal of Computational
and Graphical Statistics
,
19
, 46 - 61.
Green, P.J. (1985) Peeling data. In S. Kotz and N.L. Johnson (eds),
Encyclopedia of Statistical
Science, Volume 6
, pp. 660 - 664. New York: John Wiley & Sons, Inc.
Greenacre, M.J. (1984)
Theory and Applications of Corresepondence Analysis
. London: Academic
Press.
Greenacre, M.J. (1988) Correspondence analysis of multivariate categorical data by weighted least
squares.
Biometrika
,
75
, 457 - 467.
Greenacre, M.J. (2007)
Correspondence Analysis in Practice
(2nd edition). Boca Raton, FL:
Chapman & Hall/CRC.
Heiser, W.J. and De Leeuw, J. (1977)
How to use SMACOF-1
. Research Report. Leiden: Depart-
ment of Data Theory, University of Leiden.
Hills, M. (1969) On looking at large correlation matrices.
Biometrika
,
56
, 249 - 253.
Hirschfeld, H.O. (1935) A connection between correlation and contingency.
Proceedings of the
Cambridge Philosophical Society
,
31
, 520 - 524.
Hyndman, R.J. (1996) Computing and graphing highest density regions.
American Statistician
,
50
,
120 - 126.
Jolliffe, I.T. (2002)
Principal Component Analysis
(2nd edition). New York: Springer.
Jorion, P. (1997)
Value at Risk
. New York: McGraw-Hill.
Kempton, R.A. (1984) The use of biplots in interpreting variety by environment interactions.
Journal of Agricultural Science, Cambridge
,
103
, 123 - 135.
Krzanowski, W.J. (2004) Biplots for multifactorial analysis of distance.
Biometrics
,
60
, 517 - 524.
Lawley, D.N. and Maxwell, A.E. (1971)
Factor Analysis as a Statistical Method
(2nd edition).
London: Butterworths.
Le Roux, B. and Rouanet, H. (2004)
Geometric Data Analysis: From Correspondence Analysis to
Structured Data
. Dordrecht: Kluwer.
Le Roux, N.J. and Gardner, S. (2005) Analysing your multivariate data as a pictorial: a case for
applying biplot methodology?
International Statistical Review
,
73
, 365 - 387.
Liu, R.Y., Parelius, J.M. and Singh, K. (1999) Multivariate analysis by data depth: descriptive
statistics, graphics and inference.
Annals of Statistics
,
27
, 783 - 858.
McNabb, R. and Wass, V. (1997) Male-female salary differentials in British universities.
Oxford
Economic Papers
, New Series,
49
, 328 - 343.
Pison, G., Struyf, A. and Rousseeuw, P.J. (1999) Displaying a clustering with CLUSPLOT.
Com-
putational Statistics and Data Analysis
,
30
, 381 -392.
R Development Core Team (2009)
R: A Language and Environment for Statistical Computing
.
Vienna: R Foundation for Statistical Computing. http://www.R-project.org