Tree-Growing for the Multivariate Model: The RECPAM Approach
The RECPAM approach is applied to the multivariate normal model. Tree-structured predictors are built for the multivariate mean, the correlation matrix and regression coefficients representing a treatment-outcome relationship. Several cases of special interest are discussed.
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- Sonquist, J.A. and Morgan, J.N. (1964). The detection of interaction effects. Ann Arbor: Institute for Social Research, University of Michigan.Google Scholar
- Breiman, L., Friedman, J.H., Olshen, R.A. and Stone, C.J. (1984). Classification and Regression Trees. The Waldsworth International Group, Belmont, California.Google Scholar
- Ciampi, A., Chang, C.H., Hogg, S.A. and McKinney, S. (1987). Recursive Partition: A versatile method for exploratory data analysis in Biostatistics. Joshi Feistschrift, Vol. 5, Biostatistics, I.B. Mac Neil and G.J. Umphrey (eds), 23-50.Google Scholar
- Ciampi, A., Zhiyi Lou, Qian Lin and A. Negassa (1991) Recursive Partition and Amalgamation with the exponential family: theory and applications. Applied Stochastic Processes and Data Analysis, 7:121–137.Google Scholar
- Ciampi, A., du Berger, R., Taylor, G. and Thiffault, J. (1991). Treestructured multi-variate regression. Symbolic-numeric data analysis and learning, New York, Nova Science Publ. Inc., 263-270Google Scholar