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References
                              446
                              Naik, D.N. and Khattree, R. (1996). Revisiting Olympic track records:
                                Some practical considerations in the principal component analysis. Amer.
                                Statistician, 50, 140–144.
                              Nash, J.C. and Lefkovitch, L.P. (1976). Principal components and regres-
                                sion by singular value decomposition on a small computer. Appl. Statist.,
                                25, 210–216.
                              Nel, D.G. and Pienaar, I. (1998). The decomposition of the Behrens-Fisher
                                statistic in q-dimensional common principal common submodels. Ann.
                                Inst. Stat. Math., 50, 241–252.
                              Nelder, J.A. (1985). An alternative interpretation of the singular-value
                                decomposition in regression. Amer. Statistician, 39, 63–64.
                              Neuenschwander, B.E. and Flury, B.D. (2000). Common principal compo-
                                nents for dependent random vectors. J. Mult. Anal., 75, 163–183.
                              Nomikos, P. and MacGregor, J.F. (1995). Multivariate SPC charts for
                                monitoring batch processes. Technometrics, 37, 41–59.
                              North, G.R., Bell, T.L., Cahalan, R.F. and Moeng, F.J. (1982). Sampling
                                errors in the estimation of empirical orthogonal functions. Mon. Weather
                                Rev., 110, 699–706.
                              North, G.R. and Wu, Q. (2001). Detecting climate signals using space-time
                                EOFs. J. Climate, 14, 1839–1863.
                              Obukhov, A.M. (1947). Statistically homogeneous fields on a sphere. Usp.
                                Mat. Nauk., 2, 196–198.
                              Oca˜na, F.A., Aguilera, A.M. and Valderrama, M.J. (1999). Functional
                                principal components analysis by choice of norms. J. Mult. Anal., 71,
                                262–276.
                              Ogasawara, H. (2000). Some relationships between factors and components.
                                Psychometrika, 65, 167–185.
                              O’Hagan, A. (1984). Motivating principal components, and a stronger
                                optimality result. Statistician, 33, 313–315.
                              O’Hagan, A. (1994). Kendall’s Advanced Theory of Statistics. Volume 2B
                                Bayesian Inference. London: Arnold.
                              Okamoto, M. (1969). Optimality of principal components. In Multivariate
                                Analysis II , ed. P. R. Krishnaiah, 673–685. New York: Academic Press.
                              Oman, S.D. (1978). A Bayesian comparison of some estimators used in
                                linear regression with multicollinear data. Commun. Statist., A7, 517–
                                534.
                              Oman, S.D. (1991). Random calibration with many measurements: An
                                application of Stein estimation. Technometrics, 33, 187–195.
                              Osmond, C. (1985). Biplot models applied to cancer mortality rates. Appl.
                                Statist., 34, 63–70.
                              Ottestad, P. (1975). Component analysis: An alternative system. Int. Stat.
                                Rev., 43, 83–107.
                              Overland, J.E. and Preisendorfer, R.W. (1982). A significance test for prin-
                                cipal components applied to a cyclone climatology. Mon. Weather Rev.,
                                110, 1–4.
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