A distance based regression model for prediction with mixed data

Communications in Statistics - Theory and Methods

Volumn 19, Issue 6, 1990, Pages 2261-2279

  Cuadras, C M ^a   Arenas, C ^b  

^a UNIVERSITY OF BARCELONA   (Spain)

^b NONE

Author keywords

coordinate analysis; distance analysis; mixed qualitative and quantitative data; multiple linear regression; principal; principal component regression

Indexed keywords

EID: 0000611709     PISSN: 03610926     EISSN: 1532415X     Source Type: Journal    
DOI: 10.1080/03610929008830319     Document Type: Article

References (32)

1. Abrahamse, A. F. and Kisch, A. I. (1975), Health status age : an age predictive health status index. Rand. R-1626-OEO. Santa Monica, California
2. Atkinson, C. and Mitchell, A. F. S. (1981), “Rao’s distance measure”, Sankhya, 43A,345-365
3. Burbea, J. and Rao, C. R. (1982), “Entropy differential metric, distance and divergence measures in probability spaces: a unified approach”, J. of Multivariate Analysis, 12,575-596
4. Cuadras, C. M. (1988a), “Métodos estadisticos aplica-bles a la reconstrucción prehistdrica”, Munibe, 6,25-33
5. Cuadras, C. M. (1988b), “Distancias estadisticas”, Estadistica Española, 119,295-378
6. Cuadras, C. M. (1989), “Distance analysis in discrimination and classification using both continuous and categorical variables”. In: Statistical Data Analysis and Inference (Y. Dodge, ed.). North-Holland, Pu. Co., 459–473
7. Daudin, J. J. (1980), “Regression qualitative : choix de l'espace predicteur”. In: Data Analysis and Informatics (E. Diday et al., eds.). North-Holland Pu. Co
8. Gower, J. C. (1966), “Some distance properties of latent root and vector methods in multivariate analysis”, Biometrika, 53,315-328
9. Gower, J. C. (1968), “Adding a point to vector diagrams in multivariate analysis”, Biometrika, 55,582-585
10. Gower, J. C. (1971), “A general coefficient of similarity and some of its properties”, Biometrics, 27, 857–-874
11. Hill, R. C., Fomby, T. B. and Johnson, S. R. (1977), “Component selection norms for principal components regression”, Commun. Stat, Theor. Methods A, 6, 309–334
12. Jollife, I. T. (1986), Principal component analysis. New York: Springer-Verlag
13. Kiers, H. A. L. (1988), “Principal component analysis on a mixture of quantitative and qualitative data based on generalized correlation coefficients”. In: The many faces of Multivariate Analysis (M. G. H. Jansen and W. H. van Schuur, eds.). University of Groningen, 67–81
14. Kiers, H. A. L. (1989), Three-way methods for the analysis of qualitative and quantitative two-way data, DSWO Press, University of Leiden, Leiden
15. Knoke, J. D. (1982), “Discriminant analysis with discrete and continuous variables”, Biometrics, 38,191-200
16. Krzanowski, W. J. (1975), “Discrimination and classification using both binary and continuous variables”, JASA, 70,782-790
17. Krzanowski, W. J. (1983), “Distance between populations using mixed continuous and categorical variables”, Biometrika, 79,235-243
18. Krzanowski, W. J. (1986), “Multiple discriminant analysis in the presence of mixed continuous and categorical data”, Comp. & Maths. with Appls., 12A,179-185
19. Lauritzen, S.L. and Wermuth, N. (1989), “Graphical models for associations between variables, some of which are qualitative and some quantitative”, Ann. Statist., 17(1), 31–57
20. Lott, W. F. (1973), “The optimal set of principal component restrictions on a least-squares regression”, Commun. Stat., 2(5), 449–464
21. Mardia, K. V., Kent, J. T. and Bibby, J. M. (1979), Multivariate Analysis. London : Academic Press
22. Oiler, J. M. (1989), “Some geometrical aspects on data analysis and statistics”. In: Statistical Data Analysis and Inference (Y. Dodge, ed.). North Holland Pu. Co., 41–58
23. Oller, J. M. and Cuadras, C.M. (1985), “Rao’s distance for negative multinomial distributions”, Sankhya, 47A,75-83
24. Rao, C.R. (1945) “Information and the accuracy attainable in the estimation of statistical parameters”. Bull. Cal. Math. Soc.,37,81-91
25. Roskam, E. E. (1980), “Nonmetric analysis of linear models”. In: Data Analysis and Informatics (E. Diday et al., eds). North-Holland Pu. Co.,83-99
26. SAS/IML (1985), User's guide. SAS Institute Inc. Cary, North Carolina
27. Seber, G. A. F. (1984), Multivariate Observations. New York: J. Wiley
28. Soofi, E. S. (1988), “Principal component regression under exchangeability”, Commun. Stat. Theor. Methods A, 17,1717-1733
29. Young, F. W. (1981), “Quantitative analysis of qualitative data”, Psychometrika, 46, 357–388
30. Young, F. W., de Leeuw, J. and Takane, Y. (1976), “Regression with qualitative and quantitative variables : an alternating least squares method with optimal scaling features”, Psychometrika, 41, 505–529
31. Young, F. W., Takane, Y. and de Leeuw, J. (1978), “The principal components of mixed measurement level multivariate data : an alternating least squares method with optimal scaling features”, Psychometrika, 43,279-281
32. Weisberg, S. (1985), Applied Linear Regression. New York: J. Wiley