•   •   •   •

Download the Paper (598 K, PDF file) - January 30, 2007 Tell a colleague about it. Printing Tips: Select 'print as image' in the Acrobat print dialog if you have trouble printing.

ABSTRACT:
Homogeneity analysis combines maximizing the correlations between variables of a multivariate data set with that of optimal scaling. In this article we present methodological and practical issues of the R package homals which performs homogeneity analysis and various extensions. By setting rank constraints nonlinear principal component analysis can be performed. The variables can be partitioned into sets such that homogeneity analysis is extended to nonlinear canonical correlation analysis or to predictive models which emulate discriminant analysis and regression models. For each model the scale level of the variables can be taken into account by setting level constraints. All algorithms allow for missing values.

SUGGESTED CITATION:
Jan de Leeuw and Patrick Mair, "Homogeneity Analysis in R: The Package homals" (January 30, 2007). Department of Statistics, UCLA. Department of Statistics Papers. Paper 2007010117.
http://repositories.cdlib.org/uclastat/papers/2007010117